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23 results on 'LN cat08778a'

1. Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education.

Author

Lacave, Carmen, Molina, Ana Isabel, and Lacave, Carmen

Subjects
Research & information: general, Mathematics & science, Alzheimer's disease, dementia, functional data analysis, functional depth, statistical data depth, symmetry, elemental information matrix, gamma distribution, poisson distribution, D-optimization, misspecification, machine learning, modeling, programming, text analysis, remote rehabilitation, recommender system, stroke, fuzzy logic, telemedicine, collaborative learning, collaborative work, genetic algorithms, group formation, personality traits, computer-supported cooperative learning, non-parametric statistics, predictive methods, supervised classification, random methods, after-school exercise, academic performance, structural relationship, quantile regression, instrumental variable quantile regression, vitamin D, decision making, anthropometric parameters, optimal experimental design, bioimpedance, impedance spectroscopy, algorithm, competency-based model, didactic planning, ontology, natural language processing, Bloom's taxonomy, retina, fundus image, retinal vasculature, retinal disorders, semantic segmentation, learning behavior, student performance prediction, deep neural network (DNN), recurrent neural network (RNN), educational data mining (EDM), probabilistic graphical models, bayesian networks, value-based potentials, approximate inference, medical applications, electrocardiogram signal, discriminative convolutional sparse coding, dictionary filter learning, linear SVM, student dropout, Feature Selection, Artificial Neural Networks, Support Vector Machines, decision trees, logistic regression, ECG, mental fatigue, signal analysis, classification, OpenMarkov, Bayesian Networks, d-separation, inference, Learning Bayesian Networks, continuous assessment, Bayesian networks, artificial neural networks, influenza-like illness, COVID-19, Arabic sentiment analysis, disease classification, Facebook, Algerian dialect, mobile computing, dual tasking, cognitive decline, human motion tracking, gait analysis, n/a
Abstract

Summary: The present reprint contains all of the articles accepted and published in the Special Issue " Advances in Artificial Intelligence and Statistical Techniques with Applications to Health and Education" from the MDPI journal Mathematics. This Special Issue aims to develop more efficient and effective approaches to healthcare and education, leveraging the increasing availability of big data and advancements in artificial intelligence. By sharing new methods, applications, and case studies, this reprint is dedicated to the development of innovative solutions that improve healthcare and education for all. The topics addressed in this Special Issue cover a wide range of areas, including data mining, machine learning, learning analytics, prediction methods, pattern recognition, decision analysis, probabilistic reasoning, fuzzy systems, student or patient modelling, adaptive systems, collaborative systems, recommendation systems, experimental design, and empirical study cases. We hope that this reprint will enable the scientific community in both medicine and education to leverage the techniques from statistics and artificial intelligence to drive significant advances in their respective fields. These approaches hold promise for improving patient outcomes and enhancing the quality of education for students around the world.

2. Advances in Autism Research.

Author

Narzisi, Antonio and Narzisi, Antonio

Subjects
Medicine, Neurosciences, autism spectrum disorder, infants, frontal EEG alpha asymmetry, early detection, autism spectrum disorders, toddlers, eye tracking, joint attention, longitudinal, regression, cytokines, PAI-1, neuroinflammation, gastrointestinal, autism, literature review, comorbidity, early intervention, early intensive behavioral intervention, behavioral intervention, First Year Inventory, early screening, risk, cross-cultural generalisability, validity, preschool teachers, self-efficacy, knowledge, belief, skills, identify, autism spectrum disorder (ASD), level 1 and level 2 screening tools, systematic review, COSMIN, PRISMA, screening, infection, prion, meta-analysis, motion analysis, video signal processing, neurodevelopmental disorders, infant screening, n/a, developmental language disorder, semantic features, word learning, central coherence, biomarker, p-cresol, mouse social behavior, dopamine, ASD, vision, proprioception, self-motion, immersive virtual reality, IVR, HMD, technology, persuasive text writing, perspective-taking, adolescence, intervention, sign language, imitation, cognition, language acquisition, prevalence estimate, predictors, surveillance review, Autism Spectrum Disorder (ASD), early intensive intervention, developmental trajectories, moderators and mediators of intervention, psychosis, schizophrenia, psychopathology, AQ, accuracy, attention to detail, self-awareness, insight, preconception risk factor, Gilles de la Tourette, obsession, compulsion, social behavior, social impairment, sensory profile, sensory responsiveness, feeding problems, short sensory profile (SSP), sensory experience questionnaire (SEQ), coronavirus, 2019-nCoV, neurodevelopment, child and adolescent psychiatry, mental health prevention, Asperger syndrome, adults, cerebrospinal fluid, antibodies, blood-brain barrier, GAD65, Early Start Denver Model, high-risk infants, motor development, high-functioning autism, language, experience, communication, autonomic nervous system, wearable technologies, EEG, theory of mind, adults and adolescents, human figure drawings, Draw-a-Man, drawings maturity, social perception, ERP, reward response, RewP, sensitization, social skills intervention, PEERS®, adulthood, diagnosis, autistic traits, action observation, action prediction, context, priors, hypothalamus, amygdala, oxytocin, social cognition, social interaction, affiliative behavior, neuroimaging, COVID-19, challenging behavior, dental care, oral health, medical procedures, ICT, wearable sensors, migration, Europe, health system, autism in adulthood, intellectual disability, regressive autism, epilepsy, challenging behaviors, empathy, executive functions, attention deficit and hyperactivity disorder, disruptive behavior disorders, alexithymia, anxiety, depression, TAS-20, TSIA, parents, broader autism phenotype, autistic-like features, social-cognitive development, stereotypical behaviors, visual impairment, language profiles, grammatical comprehension, cannabinoids, cannabidiol, cannabidivarin, THC, problem behaviors, sleep, hyperactivity, side effects, motor performance skills, Gulf, BOT-2, machine learning, employment, telehealth, ABA, RCT, cortisol, group activity, stress, art, assessment, sensorimotor integration, postural balance, false positive report probability (FPRP), Bayesian false-discovery probability (BFDP), Genome-Wide Association Studies (GWAS), microbiome, metabolomics, study design, biomarker discovery, precise medicine, bipolar disorder, suicidal ideation, suicidal attempts
Abstract

Summary: This book represents one of the most up-to-date collections of articles on clinical practice and research in the field of Autism Spectrum Disorders (ASD). The scholars who contributed to this book are experts in their field, carrying out cutting edge research in prestigious institutes worldwide (e.g., Harvard Medical School, University of California, MIND Institute, King's College, Karolinska Institute, and many others). The book addressed many topics, including (1) The COVID-19 pandemic; (2) Epidemiology and prevalence; (3) Screening and early behavioral markers; (4) Diagnostic and phenotypic profile; (5) Treatment and intervention; (6) Etiopathogenesis (biomarkers, biology, and genetic, epigenetic, and risk factors); (7) Comorbidity; (8) Adulthood; and (9) Broader Autism Phenotype (BAP). This book testifies to the complexity of performing research in the field of ASD. The published contributions underline areas of progress and ongoing challenges in which more certain data is expected in the coming years. It would be desirable that experts, clinicians, researchers, and trainees could have the opportunity to read this updated text describing the challenging heterogeneity of Autism Spectrum Disorder.

3. Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics.

Author

Tutone, Marco, Almerico, Anna Maria, and Tutone, Marco

Subjects
Research & information: general, Chemistry, 3D-QSAR, pharmacophore modeling, ligand-based model, HDACs, isoform-selective histone deacetylase inhibitors, aminophenylbenzamide, hERG toxicity, drug discovery, fingerprints, machine learning, deep learning, gene expression signature, drug repositioning approaches, RNA expression regulation, high-throughput virtual screening, dual-target lead discovery, neurodegenerative disorders, Alzheimer's disease, dual mode of action, multi-modal, nicotinic acetylcholine receptor, acetylcholinesterase, molecular docking, methotrexate, drug resistance, human dihydrofolate reductase, virtual screening, molecular dynamics simulation, epitope binning, epitope mapping, epitope prediction, antibody:antigen interactions, protein docking, glycoprotein D (gD), herpes simplex virus fusion proteins, Src inhibitors, pharmacophore model, molecular dynamics simulations, in silico, COX-2 inhibitors, molecular modeling, sodium-glucose co-transporters 2, FimH, uropathogenic bacteria, urinary tract infections, diabetes, drug-resistance mutations, HIV-2 protease, structural characterization, induced structural deformations, SARS-CoV-2, COVID-19, multiprotein inhibiting natural compounds, MD simulation, 3CL-Pro, antivirals, docking simulations, drug repurposing, consensus models, binding space, isomeric space, MRP4, SNPs, variants, protein threading modeling, molecular dynamics, binding site, hTSPO, PK11195, cholesterol, homology modeling, molecular dynamics (MD) simulation, carbon nanotubes, Stone-Wales defects, haeckelite defects, doxorubicin encapsulation, drug delivery system, binding free energies, noncovalent interactions, main protease, mutants, inhibitors, PF-00835231, Mycobacterium tuberculosis, tuberculosis, proteasome, natural compounds, multiscale, multitargeting, polypharmacology, computational biology, drug repositioning, structural bioinformatics, proteomic signature, skin aging, oxidative stress, aging progression mechanism, genome-wide genetic and epigenetic network (GWGEN), systems medicine design, multiple-molecule drug, immunoproteasome, non-covalent inhibitors, MD binding, metadynamics, induced-fit docking, n/a
Abstract

Summary: This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs.

4. COVID-19. Impact on Public Health and Healthcare.

Author

Batra, Kavita, Sharma, Manoj, and Batra, Kavita

Subjects
Humanities, Social interaction, COVID-19, novel coronavirus, social lockdown, protection motivation theory, health behavior, health communication, pregnant woman, coronavirus, infectious disease transmission, vertical transmission, obstetric management, SARS-CoV-2, systematic review, computerized tomography, pneumonia, risk factors, echocardiography, healthcare, mental health, Impact of event scale, negative attitude, Saudi Arabian females, health services, cost, manual therapy, chiropractic, osteopathy, physiotherapy, direct RT-PCR, molecular detection, dental care, dental health services, dental visits, dental service use, postponed dental visits, check-up, dental examination, pain, dental complaints, oral health, Saudi Arabia, blood donors, seroprevalence, ELISA, antibodies, lockdown, multi-theory model, behavior change, pandemic, handwashing, young adults, college students, protective behavior changes, individual, family, environmental factor, COVID-19 spreading, online survey, awareness and knowledge, ships, seafarers, SARS-COV-2, anxiety, depression, stress, suicidal ideation, students, time-series, ARIMA, forecasting, confirmed cases, infectious disease, international cruises, health policy and regulation, control strategies, international cooperation, global health governance, ICF, healthcare services, interprofessional education, medical students, pharmacy students, telehealth, older adults, artificial intelligence, machine learning, bibliometric analysis, health, novel design, fabrication, automated dispenser, LDR based controller, reduction of COVID-19 spread, psychological symptom, college student, avoidance of infection, social distancing, free tickets for the aged, subway use demand, e-learning, youth and children health, visual health, myopia, routine care, global pandemic, role conflict, role ambiguity, social support, dental precautions, dental students, India, infection control, knowledge, perception, survey, face masks, young people, behaviors, dentist, infection control practices, concerns, dental practice, social isolation, social connectedness, loneliness, technology, internet, smartphones, m-health, severe acute respiratory syndrome, post-graduate year training, self-efficacy, emotional traits, Coronavirus, prevention, community, public health nurse, telephone consultation, vaccine literacy, Japan, family carers for older adults, sustainable ageing society, health communications, mass media, HCWs, personality traits, intolerance of uncertainty, coping strategies, perceived stress, resilience, migration, refugees, fear, modeling, data analysis, assessment, effectiveness, incidence rate, restriction, epidemic pattern, exponential growth, basic reproduction number (R0), spatio-temporal analysis, demographic risk factor, observational study, public health, Southeast Asia (SEA), vaccination rate, basic reproduction number, SARS-CoV, African American, COVID-19 vaccine, vaccine hesitancy, vaccine hesitant, text classification, SARS-CoV-2 infection, survival rate, hospitalized patients, Hidalgo Mexico, multimorbidity, vaccination, level 1 trauma, health care workers, information source trust, COVID-19 stressor, global south
Abstract

Summary: This compendium describes the impact of COVID-19 pandemic on all aspects of people lives. Data presented in this collection will be useful to understand the disruption in healthcare, learning, and socio-economic aspects amidst the pandemic. The sooner we begin to understand the impact, the better placed we will be to address the unmet needs of vulnerable population groups.

5. Data Science in Healthcare.

Author

Hulsen, Tim and Hulsen, Tim

Subjects
Medicine, Pharmacology, data sharing, data management, data science, big data, healthcare, depression, psychological treatment, task sharing, primary care, pilot study, non-specialist health worker, training, digital technology, mental health, COVID-19, SARS-CoV-2, pneumonia, computed tomography, case fatality rate, social distancing, smoking, metabolically healthy obese phenotype, metabolic syndrome, obesity, coronavirus, machine learning, social media, apache spark, Twitter, Arabic language, distributed computing, smart cities, smart healthcare, smart governance, Triple Bottom Line (TBL), thoracic pain, tree classification, cross-validation, hand-foot-and-mouth disease, early-warning model, neural network, genetic algorithm, sentinel surveillance system, outbreak prediction, artificial intelligence, vascular access surveillance, arteriovenous fistula, end stage kidney disease, dialysis, kidney failure, chronic kidney disease (CKD), end-stage kidney disease (ESKD), kidney replacement therapy (KRT), risk prediction, naïve Bayes classifiers, precision medicine, machine learning models, data exploratory techniques, breast cancer diagnosis, tumors classification, n/a
Abstract

Summary: Data science is an interdisciplinary field that applies numerous techniques, such as machine learning, neural networks, and deep learning, to create value based on extracting knowledge and insights from available data. Advances in data science have a significant impact on healthcare. While advances in the sharing of medical information result in better and earlier diagnoses as well as more patient-tailored treatments, information management is also affected by trends such as increased patient centricity (with shared decision making), self-care (e.g., using wearables), and integrated care delivery. The delivery of health services is being revolutionized through the sharing and integration of health data across organizational boundaries. Via data science, researchers can deliver new approaches to merge, analyze, and process complex data and gain more actionable insights, understanding, and knowledge at the individual and population levels. This Special Issue focuses on how data science is used in healthcare (e.g., through predictive modeling) and on related topics, such as data sharing and data management.

6. Disasters Preparedness and Emergency Response: Prevention, Surveillance and Mitigation Planning.

Author

Goniewicz, Mariusz and Goniewicz, Mariusz

Subjects
Public health & preventive medicine, alcohol, ethanol, pedestrians, traffic accidents, flood, disasters, emergency preparedness, hospital preparedness, Saudi Arabia, first aid, education, basic life support, cardiopulmonary resuscitation, feedback device, simulation, quality, skill retention, motivation, chest recoil, mannequin, contact tracing, ethics, pandemic, psychology, public education, public health, alternative care facilities, flexible surge capacity, major incidents and disasters, surge capacity, information and communication technology, smart disaster management system, Internet of Things, disaster, flood early warning, flood response, community volunteerism, disaster volunteer group, resilience, governance and planning, disaster management, sustainability, security, safety, crisis management, risk management, emergencies, health emergency, management, disaster legislation, preparedness, COVID-19, stress, stressors, cortisol, medical simulation, low-fidelity simulation, high-fidelity simulation, stress appraisal questionnaire, KOS-B, nursing, machine learning, health geomatics, geographic information system, emergency medical services, spatial filtering, geo-AI, resources management
Abstract

Summary: This Special Issue welcomes research papers on new approaches that have been applied or are under development to improve preparedness and emergency response. We especially encourage the submission of inter-disciplinary and crosscutting research. We also encourage the submission of manuscripts that focus on various types of disasters, disaster and emergency research, and on policy or management solutions at multiple scales.

7. Efficiency and Optimization of Buildings Energy Consumption: Volume II.

Author

Orosa, Josรฉ A. and Orosa, Josรฉ A.

Subjects
Research & information: general, Physics, ventilation, energy, COVID-19, procedure, building, ISO, energy consumption, building construction, Passivhaus, affordable housing, neural network, LSTM, MLP, thermal inertia, building performance, artificial intelligence, artificial neural network, demand-side management, evolutionary computing, non-intrusive appliance load monitoring, parallel computing, smart grid, smart house, cellular concrete, lightweight materials, thermal conductivity, electricity, dynamic simulation, housing, climate change, weather controlled central system, energy saving, thermal improved of buildings, new energy technologies, sustainable buildings, energy efficiency, heat loss coefficient, machine learning, XGBoost, SVR, load disaggregation, multi-scale, attention mechanism, residual network, energy savings, daylighting, photovoltaic system, EnergyPlus, Homer PRO, Net Zero Energy Buildings, solar radiation, support vector machine, heuristic algorithm, renewable energy, solar energy systems, n/a
Abstract

Summary: This reprint, as a continuation of a previous Special Issue entitled "Efficiency and Optimization of Buildings Energy Consumption", gives an up-to-date overview of new technologies based on Machine Learning (ML) and Internet of Things (IoT) procedures to improve the mathematical approach of algorithms that allow control systems to be improved with the aim of reducing housing sector energy consumption.

8. Emerging Trends in Energy Economics.

Author

Gogas, Periklis, Papadimitriou, Theophilos, and Gogas, Periklis

Subjects
Research & information: general, Physics, economic growth, innovation activity, globalization, international trade, uncertainty, spillovers, realized variance, crude oil, forecasting, bibliometric analysis, development economics, energy, renewable energy, energy-growth nexus, sustainable economy, new economics, critical review, natural gas, spot price, machine learning, energy commodities, financial crises, Brent, WTI, gasoline, clustering, t-SNE, COVID-19 pandemic, target model, Greek wholesale electricity market, day-ahead market, intraday market, balancing market, trading volumes, COVID-19, pandemic, energy market volatility, announcements, deaths, infections, load forecasting, load series, mode decomposition, extreme learning machine, kernel density estimation, geopolitical risk, renewable energy sources, energy production, ARDL, GDP, CO2 emissions, n/a
Abstract

Summary: Energy and its economic implications have been in the spotlight of policymakers, academics, traders, speculators and the industry for decades now. It has been an active research topic for more than 150 years. From the 19th century, the problem of creating, processing, storing and transporting energy was well defined. The issues of efficiently producing, pricing, distributing, and forecasting the demand, supply and prices of energy-related products and services are central to most modern economies irrespective of their level of development. These issues are apparent in times of relative tranquility in the respective markets but become central for all stakeholders in times of turbulence. This volume focuses on emerging methodologies of analysis, description, modelling, and forecasting in the topical area of Energy Economics. Includes emerging and innovative methodological approaches from the areas of machine learning, artificial intelligence, econometrics, and statistics aimed to model, describe or forecast the energy markets at all levels. Additionally, the volume also presents a bibliographical review, summarizes and compares results of different studies in the energy-sustainable economic growth and development nexus. The practical importance of the results to all energy market stakeholders in terms of regulating, pricing, and distributing energy is evident. Theoretical robustness, methodological innovation, and possible direct applicability of the conclusions were the basic requirements for research work to be included in this publication.

9. Entropy in Real-World Datasets and Its Impact on Machine Learning.

Author

Kozak, Jan, Juszczuk, Przemysล‚aw, and Kozak, Jan

Subjects
Information technology industries, Computer science, machine learning, optical networks, imbalanced data, one-class classification, entropy measure, real-world data, preprocessing, decision table, classification, query set, decision tree, differential cryptanalysis, metaheuristics, symmetric block ciphers, memetic algorithms, DES, simulated annealing, COVID-19, vaccination, agent-based modelling, dynamic stochastic general equilibrium models, scenario analyses, validation of results, stock index forecasting, CEEMDAN, ADF, ARMA, LSTM, hybrid model, classification measure, quality of classification, quality measure, preference-driven classification, fast iterative filtering, parameter adaptive refined composite multiscale fluctuation-based dispersion entropy, rotating machinery, fault diagnosis, short-term demand prediction, bike-sharing, travel characteristics analysis, hybrid TCN-GRU model, distributed data, decision tables, information systems, decision trees, decision rules, tests, reducts, association rules, Pawlak conflict analysis model, independent data sources, coalitions, dispersed data, length, support, greedy heuristics, feature selection, rough sets, action units, automatic translation, sign language, entropy of real data
Abstract

Summary: The topic of the reprint is very important nowadays, because ever-evolving machine learning techniques make it possible to obtain better real-world data. Therefore, this reprint contains information related to real data in fields such as automatic sign language translation, bike-sharing travel characteristics, stock index, sports data, fake news data, and more. However, it should be noted that the reprint also contains a lot of information on new developments in machine learning, new algorithms, algorithm modifications, and a new measure of classification quality assessment that also takes into account the preferences of the decision maker.

10. Feature Papers "Age-Friendly Cities & Communities: State of the Art and Future Perspectives"

Author

van Hoof, Joost, Marston, Hannah R., and van Hoof, Joost

Subjects
Humanities, Social interaction, age-friendly cities, physical environment/space, urban ageing, gentrification, displacement, aging in place, physical activity, aging, social isolation, cycling, walking, ICT, older adults, patent, personalised ageing, quality of life, review, smart ageing, social robots, ambient assisted living, machine learning, older adults care, daily life activities monitoring, technology limitation and acceptance, care services models, older citizens, ageing, technology, digital, smart cities initiatives, smart city, Romania, public policies on smart cities, evaluating smart cities initiatives, older people, connectedness, social relationships, later life, age-friendliness, community, digital technology, loneliness, isolation, intergenerational communication, gerontology, family, cross-cultural research, qualitative research, housing, elderly, assisted living facilities, seniors, homes, group living, dwellings, regulations, rebellion, governance, law, survey, questionnaire, validation, age-friendly, AFCCQ, consultation-liaison psychiatry, psycho-geriatrics, general hospital, age-friendly urban public transport, smart mobility, age-friendly transport, mobility justice, health, indicators, planning, tools, spatial, neighbourhoods, e-health, urban planning, smart ecosystem, gerontechnology, age in place, coronavirus, COVID-19, design hacking, internet of things, human-centered design, smart cities, digital citizenship, urbanisation, participatory action research, cluster analysis, thermal comfort, design guidelines, heating, cooling, participatory video design, participation, person-centered care, co-creation, perspective of older adults, quality improvement, use of technology, Tฤmaki Makaurau Auckland, Polynesian population, relational leadership, Te Tiriti o Waitangi, prisons, prisoners, older offenders, ex-prisoners, age-friendly cities and communities, Kazan, Russia, health information, ageism, Cochrane, evidence-based, medicines, consumers, awareness, Age-Friendly Cities, photovoice, healthy ageing, active ageing, social inclusion, UK, long-term care, dementia, physical environment, social environment, organizational environment, environmental design, policy, case studies, Global Network of Age-Friendly Cities and Communities, World Health Organization, social prescribing, wearable technology, digital data layer, age-friendly communities, citizen science, well-being, gender, Coronavirus, human centred design, rural planning, smart islands, age-friendly homes, innovation, experiments, n/a
Abstract

Summary: The "Age-Friendly Cities & Communities: States of the Art and Future Perspectives" publication presents contemporary, innovative, and insightful narratives, debates, and frameworks based on an international collection of papers from scholars spanning the fields of gerontology, social sciences, architecture, computer science, and gerontechnology. This extensive collection of papers aims to move the narrative and debates forward in this interdisciplinary field of age-friendly cities and communities.

11. Industrial Applications: New Solutions for the New Era.

Author

de Sales Guerra Tsuzuki, Marcos, Pessoa, Marcosiris Amorim de Oliveira, Acรกcio de Andrade, Alexandre, and de Sales Guerra Tsuzuki, Marcos

Subjects
Technology: general issues, History of engineering & technology, induction machines, electrical machines, vector control, SVPWM modulation, frequency inverter, artificial intelligence, photovoltaics, fault detection, machine learning, operation and maintenance, renewable energy, water-in-crude oil emulsion, water content, ultrasound, propagation velocity, exoskeletons, test bench, industry, benchmarking, microgrid model-based systems engineering, service systems, goal-oriented requirements engineering, safety instrumented system, ventricular assist device Bayesian network, Petri net, control strategy, UAV, fuzzy, PID controller, ROS, Industry 4.0, database, data models, big data and analytics, asset administration shell, MLOps, digital twin, IoT, prediction, coordinate metrology, optical scanning, noise reduction, digital manufacturing, integrated inspection system, data analytics, uncertainty, convolutional neural networks, warehouse management, image classification, ensemble learning, synthetic data, depth image, electrical maintenance, COVID-19, thermography, fever, computer vision, intelligent systems
Abstract

Summary: This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section.

12. Information Technology's Role in Global Healthcare Systems.

Author

Wiesner, Martin, Schreiweis, Bjรถrn, and Wiesner, Martin

Subjects
Medicine, fever, FeverApp, ecological momentary assessment, user behavior, sociodemographic characteristics, registry, guidelines, feasibility, usability, routine health information system, health management information system, health system performance, machine learning, digital health, registry analysis, ClinicalTrials.gov, device regulation, new information technology, Technology Acceptance Model (TAM), institution, institutionalism, digital informatics, human-computer interaction, personal health informatics, consumer health data, consumer health information, self-tracking, quantified self, mHealth apps, telemonitoring, telemedicine, telecardiology, cardiology, wearable, sensors, consumer health devices, cardiovascular disease, heart failure, atrial fibrillation, mental health, psychiatry, psychiatric record, psychiatric notes, patient accessible electronic health record, PAEHR, open notes, policies, COVID-19, technology acceptance, user survey, wearable health monitor, ECG patch, personal electronic health records, technology adoption, endogenous motivations, health information privacy concern, mixed-methods, ePA, online review helpfulness, signaling theory, sentiment analysis, physician rating websites, consumer decision-making, health information technology, information exchange, hospital, market
Abstract

Summary: Over the past few decades, modern information technology has made a significant impact on people's daily lives worldwide. In the field of health care and prevention, there has been a progressing penetration of assistive health services such as personal health records, supporting apps for chronic diseases, or preventive cardiological monitoring. In 2020, the range of personal health services appeared to be almost unmanageable, accompanied by a multitude of different data formats and technical interfaces. The exchange of health-related data between different healthcare providers or platforms may therefore be difficult or even impossible. In addition, health professionals are increasingly confronted with medical data that were not acquired by themselves, but by an algorithmic "black box". Even further, externally recorded data tend to be incompatible with the data models of classical healthcare information systems.From the individual's perspective, digital services allow for the monitoring of their own health status. However, such services can also overwhelm their users, especially elderly people, with too many features or barely comprehensible information. It therefore seems highly relevant to examine whether such "always at hand" services exceed the digital literacy levels of average citizens.In this context, this reprint presents innovative, health-related applications or services emphasizing the role of user-centered information technology, with a special focus on one of the aforementioned aspects.

13. Intelligent Sensors for Human Motion Analysis.

Author

Krzeszowski, Tomasz, ลšwitoล„ski, Adam, Kepski, Michal, Calafate, Carlos Tavares, and Krzeszowski, Tomasz

Subjects
Technology: general issues, History of engineering & technology, gait recognition, biometrics, regularized discriminant analysis, particle swarm optimization, grey wolf optimization, whale optimization algorithm, FMCW, vital sign, XGBoost, MFCC, COVID-19, 3D human pose estimation, deep learning, generalization, optical sensing principle, modular sensing unit, plantar pressure measurement, gait parameters, 3D human mesh reconstruction, deep neural network, motion capture, neural networks, reconstruction, gap filling, FFNN, LSTM, BILSTM, GRU, pose estimation, movement tracking, computer vision, artificial intelligence, markerless motion capture, assessment, kinematics, development, machine learning, human action recognition, features fusion, features selection, recognition, fall risk detection, balance, Berg Balance Scale, human tracking, elderly, telemedicine, diagnosis, precedence indicator, knowledge measure, fuzzy inference, rule induction, posture detection, aggregation function, markerless, human motion analysis, gait analysis, data augmentation, skeletal data, time series classification, EMG, pattern recognition, robot, cyber-physical systems, RGB-D sensors, human motion modelling, F-Formation, Kinect v2, Azure Kinect, Zed 2i, socially occupied space, facial expression recognition, facial landmarks, action units, convolutional neural networks, graph convolutional networks, artifact classification, artifact detection, anomaly detection, 3D multi-person pose estimation, absolute poses, camera-centric coordinates, deep-learning, n/a
Abstract

Summary: The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems.

14. Mathematical Modeling and Simulation in Mechanics and Dynamic Systems.

Author

Scutaru, Maria Luminiศ›a, Pruncu, Catalin I., and Scutaru, Maria Luminiศ›a

Subjects
Research & information: general, Mathematics & science, T-stress, X-FEM, notch, pipe, stress difference method (SDM), system of transcendental equation, computational solutions, code-based modelling approach, numerical analysis, Sine-Gordon equations, photovoltaics, thermophotovoltaics, solar energy, polymer CNTs systems, interphase section, percolation onset, mechanics, high temperature proton exchange membrane fuel cell, exergy analysis, ecological analysis, ecological coefficient of performance, SARS-CoV-2, COVID-19, SEIRD (Susceptible, Exposed, Infected and Recovered and Death), SDL, Catalonia, nanowire cantilever, stochastic model, double Lorentzian spectrum, HT-PEMFC, irreversibility, finite time thermodynamic optimization, power density, thermodynamic efficiency, geometric analogy, similarity theory, dimensional analysis, model law, heat transfer, straight bar, Deep Learning (DL), Computational Fluid Dynamics (CFD), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), turbulent flow, machine learning, deep learning, artificial neural network, ANN, PEM fuel cell, modeling, control, differentiability, fractal hydrodynamic regimes, fractal Schrödinger regimes, fractal soliton, fractal kink, "holographic implementations", cubics, apolar transport, harmonic mapping principle, period doubling scenario, state probability functions, partial aging in standby, Monte Carlo simulation, qualitative and quantitative verification of simulation model, Lagrange-d'Alembert principle, non-conservative dynamical system, Euler-Poincaré equation, helicopter model, Lie group, extended iso-geometric analysis, extended finite element method, crack, pipeline, ABAQUS, harmonic mapping, complex system dynamics, SL (2R) group, hidden symmetries, computer simulations, actual systems, transfer learning, autonomous feature extraction, n/a
Abstract

Summary: The present book contains the 16 papers accepted and published in the Special Issue "Mathematical Modeling and Simulation in Mechanics and Dynamic Systems" of the MDPI "Mathematics" journal, which cover a wide range of topics connected to the theory and applications of Modeling and Simulation of Dynamic Systems in different field. These topics include, among others, methods to model and simulate mechanical system in real engineering. It is hopped that the book will find interest and be useful for those working in the area of Modeling and Simulation of the Dynamic Systems, as well as for those with the proper mathematical background and willing to become familiar with recent advances in Dynamic Systems, which has nowadays entered almost all sectors of human life and activity.

15. Mobile Health Technologies for Ambient Assisted Living and Healthcare.

Author

Pires, Ivan Miguel and Pires, Ivan Miguel

Subjects
Information technology industries, Computer science, data privacy, taxonomy, IoT, COVID-19, mobile application, accelerometer sensor, stand-up time, total time, aging, linear-map convolutional neural network, direct acyclic graph, action recognition, spatial feature, temporal feature, frailty, home monitoring, user-centered design, usability, user experience, acceptance, activity recognition, Internet of Things, smart house, deep learning, channel state information, glaucoma screening, retinal images, segmentation, classification, precision nutrition, food plans, machine learning, food logging, Eight Hop Test, systematic review, measurement, sensors, diseases, wrist-wearable device, PPG processing, physiological parameters, web-based applications, data analysis, elderly monitoring, successful aging, gerontechnology, AAL, healthcare, prevalidation, deployment, chronic heart failure, large-scale pilot, H2020
Abstract

Summary: The use of telemedicine and mobile devices is growing, and sensors might aid in creating creative solutions. Developing these solutions is crucial for monitoring senior citizens, lifestyles, and medical procedures. This Special Issue's goal was to bring together academics and professionals in healthcare and medicine interested in using information and communication technologies (ICT) to serve people with special needs. The development of assistive technology for various users to follow sports and other activities is strongly tied to this study area. Data protection is crucial, and the development of these solutions for medical uses should be verified. The security and privacy of the information may be tied to other recognized research projects for their acceptability. ICT research has considerably improved quality of life and has fully assimilated all citizens into society through medical rehabilitation and assistive technology. The technologies and research fields that influence medical informatics include databases, networking, graphical user interfaces, data mining, machine learning, intelligent decision support systems, and specialized programming languages. Because mobile devices are commonly used for several everyday chores and are equipped with sensors that monitor various physical and physiological indicators, it is crucial to encourage the development of m-Health and e-Health solutions for healthcare practitioners. In this area, several solutions are now being developed. In addition, they can collaborate with emerging technologies for social assistance while enhancing life quality.

16. Monitoring and Promoting Physical Activity, Physical Fitness and Motor Competence in Children.

Author

Georgian, Badicu, Silva, Ana Filipa, Borges Sarmento, Hugo Miguel, and Georgian, Badicu

Subjects
flat foot, subtalar flexibility, plantar arch index, orthoses, the International Fitness Scale (IFIS), reliability, children, adolescents, Chinese, handball, motor capacity, psychological characteristics, junior players, software creation, adolescent, exercise, sport pedagogy, physical education, Mediterranean diet, emotional intelligence, physical activity, body mass index, verbal encouragement, Hoff circuit, enjoyment, mood, performance, COVID-19, lockdown, motor learning, motor skills, balance, sedentary time, sedentary pattern, cardiorespiratory fitness, ASD, postural control, rehabilitation, combat sports, physical fitness, mental health, PFI, children and adolescents, association analysis, cross-sectional survey, space-temporal orientation, general intelligence, psychomotricity, specific intervention, youth, sprint, jump, YBT, FMS, motor competence, health, monitoring and promoting, sport, sedentary behavior, obesity, well-being, active free time, factors affecting physical fitness, passive free time, Zuchora test, ActiGraph accelerometer, machine learning, walking, early childhood, cerebral palsy, therapy activation, programme, excess weight, urban environment, sedentary behaviour, socio-ecological mode, human development, motor development, motor test, motor performance, lifespan, football, sports medicine, physical exercise, physical conditioning, child, body image, self-perception, body shape questionnaire
Abstract

Summary: As we know, a large amount of research confirms that physical activity (PA), physical fitness (PF), and motor competence (MC) are associated with health benefits in individuals of all ages. Achieving a sufficient level of PA and PF will consequently further contribute to better health-related biomarkers. Moreover, holding a good MC allows better participation in PA and exercise in life, promoting greater physical literacy.It is true that the measurement of PA in children and young people is subject to several conditioning factors which threaten validity and reliability. Additionally, it is good to remember that the World Health Organization guidelines on PA and sedentary behaviour for children recommend: (1) 180 min of PA (at any intensity) for two-year old children; (2) 180 min of PA, of which 60 min is moderate-to-vigorous physical activity (MVPA), for 3- to 4-year-old children; and (3) at least 60 min of MVPA for children and adolescents from 5 to 17 years old.Therefore, understanding and developing strategies to promote PA behavior is now more important than in the past, because it is essential to improve fitness levels and MC in early ages. These strategies should cover all generations, children and youth, adults and the elderly, equally, because negative outcomes are visible in individuals of all ages.In this Special Issue, we show contributions that describe and list the link, monitoring and promotion between PA, PF, and MC.

17. Process Control and Smart Manufacturing for Industry 4.0.

Author

Yurish, Sergey Y. and Yurish, Sergey Y.

Subjects
Research & information: general, Chemistry, steel alloys, resistance spot welding, RSW, electrode wear, electrode tip-dressing, process monitoring, mushrooming, plateau forming, quality control, COVID-19, FDM, 3D printing, injection molding, personal protection, rapid prototyping, protective face shields, mechatronics line, visual servoing system, wheeled mobile robot, industrial robotic manipulator, Industry 4.0, NDT, magnetic particle inspection, optimization, condition monitoring, vibration, acoustic emission, drive train, data fusion, machine learning, product morphology, core data model, phase rule filter, phase private data model, storage system, forklift AGV, deep learning, semantic segmentation, H-Swish, community transformation, community innovation governance, ternary space, coupling and coordination analysis, lean manufacturing, lean principles, pull principle, production control mechanisms, production processes, lean implementation, batch process, partial least squares, multi-phase, multi-mode, master production scheduling, make-to-order, mathematical programming, agent-based, overtime, earliness, tardiness, equipment selection decision, business compass, energy consumption, processing time, beetle antennae search algorithm, sustainable blank dimension design, energy-saving, low-carbon, grey wolf algorithm, gas-solid, cyclone, separator, gas dynamics, erosion
Abstract

Summary: This reprint, entitled "Process Control and Smart Manufacturing for Industry 4.0", contains the extended papers from the Series of annual IFSA conferences on Automation, Robotics and Communications for Industry 4.0/5.0 (ARCI) on the following topics: Process Automation, Process Control and Monitoring, Design Principles in Industry 4.0, Smart Manufacturing and Technologies, Smart Factories, Machine Learning and Artificial Intelligence in Manufacturing. The reprint contains 13 chapters written by 54 ARCI conference participants from seven countries: China, Croatia, Denmark, Germany, Italy, Poland and Romania. This reprint will inform readers of cutting-edge developments in the field and provide effective starting points and a road map for further research and development. All chapters follow the same structure: firstly, an introduction to the specific topic under study; secondly, a description of the field, including sensing or/and measuring applications. Each chapter ends with a curated list of references, including books, journals, conference proceedings and websites. "Process Control and Smart Manufacturing for Industry 4.0" is intended for researchers and scientists from academia and industry, as well as for postgraduate students.

18. Recent Advances in Dual Disorders (Addiction and Other Mental Disorders)

Author

Torrens, Marta, Adan, Ana, and Torrens, Marta

Subjects
Medicine, Neurosciences, circadian rhythm, dual disorders, chronobiology, substance use disorders, schizophrenia, major depressive disorder, bipolar disorder, distal skin temperature, dual diagnosis, consultation liaison service, quality of life, gender, substance use disorder, genetic polymorphisms, neurocognition, chronobiological therapy, exposure to natural light, clinical course, alcohol-use disorders, personality disorders, externalizing, network analysis, antisocial personality disorder, borderline personality disorder, dual disorder, mental disorders, screening, cocaine use disorder, alcohol use disorder, substance-related disorders, treatment retention, cannabis use disorder, machine learning, dual pathology, COVID-19, care activity, pandemic, drug addiction, mental health, gambling disorder, gambling-related offenses, dropout, relapse, psychopathology, personality, substance use, psychiatric comorbidity, impulsivity, co-occurring disorders, suicidality, overdose, HIV, patient navigation, barriers to care, social determinants of health, syndemic framework, n/a
Abstract

Summary: Dual disorders, meaning the coexistence in the same individual of a substance use disorder and another mental disorder, have become an area of great interest in the fields of psychiatry and addiction and in health overall due to their high prevalence, clinical relevance and multicultural presence. This book includes a compilation of papers published between the end of 2021 and the beginning of 2023 focused on recent advances in dual disorders. The contributions present a broad look at various relevant aspects. Among them are the characterization of patients treated in different services, with special interest in the risk of overdoses, suicidal attempts and HIV, as well as the so-forgotten gender perspective and the impact of the COVID-19 pandemic on the attention of addiction centers. One of the first studies to consider the comorbidity of gambling disorders with substance use is also presented. The possible usefulness of explanatory models of machine learning for diagnosis and for performing chronobiological measurements that allow a more individualized treatment stand out among the novel contributions to the field of dual disorders. The aim of each of the contributions of this reprint is to be transferred for the benefit of clinical practice.

19. Recent Advances in Minimally Invasive Surgery.

Author

Biebl, Matthias, Alkatout, Ibrahim, and Biebl, Matthias

Subjects
Medicine, ovarian cancer, laparoscopy, minimally invasive surgery, survival, mortality, platelet-rich plasma (PRP), thin endometrium, hysteroscopy, robotic surgery, sexuality, laparoscopic hysterectomy, learning curve, quality of life, counseling, patient-doctor-relationship, body donors, surgical education, clinical anatomy, live surgery events, neuropelveology, LION procedure, genital nerves stimulation, chronic pelvic pain, esophagectomy, esophageal cancer, Ivor-Lewis procedure, health-related quality of life, cervical cancer, robotic radical hysterectomy, recurrence rate, surgery, artificial intelligence, machine learning, augmented reality, hysterectomy, NOTES, minimally invasive, systematic review, meta-analysis, pediatric surgery, fetal surgery, single-incision surgery, surgical techniques, surgical devices, open surgery, endoscopy, endoscopic surgery, cysts of the canal of Nuck, Nuck hydrocele, hydrocelectomy, TAPP, Lichtenstein, colorectal liver metastases, laparoscopic liver surgery, minimal invasive surgery, general anesthesia, anesthetics, perioperative care, laparoscopic surgery, endometrial cancer, lymphadenectomy, embryology, sentinel lymph node mapping, indocyanine green, PMMR, technical aspects, rectal cancer, mesorectal, transanal, laparoscopic, local recurrence, conversion rate, minimally invasive surgical procedures, radiotherapy, ovarian neoplasms, endometrial neoplasms, uterine cervical neoplasms, vaginal neoplasms, vulvar neoplasms, survival analysis, n/a, video feedback, video modeling, gynecology, surgical training, pelvitrainer, prolapse, pelvic floor, native tissue, pectopexy, robotic assisted surgery, pancreatic surgery, pancreaticoduodenectomy, pelvic floor repair, laparoscopic repair, vaginal repair, mesh use, VATS, pain, postoperative pain control, thoracic surgery, lung cancer, intercostal catheter, opioid, regional anaesthesia, hepatectomy, single-port laparoscopy, radiofrequency pre-coagulation, endometriosis, endometrioma surgery, ovarian reserve, anti-Müllerian hormone, spontaneous pregnancy, robotic liver resection, da Vinci, intraoperative imaging, hepatocellular cancer, real-life imaging, hepatic metastasis, COVID-19, sars-cov-2, surgical performance, 3D printing, skill assessment, snorkel mask, malabsorption, Roux-en-Y gastric bypass, one-anastomosis gastric bypass, SADI-S, biliopancreatic diversion, weight regain, hepatocellular carcinoma, cholangiocarcinoma, risk score, pelvic compartments, embryologic development, oncologic surgery, pelvic lymphonodectomy, topographic anatomy, autonomic pelvic nerves, uterine cancer, prostate cancer, diaphragmatic hernia, liver resection, hernia repair, mesh, enterothorax
Abstract

Summary: Minimally invasive surgery has become a common term in visceral as well as gynecologic surgery. It has almost evolved into its own surgical speciality over the past 20 years. Today, being firmly established in every subspeciality of visceral surgery, it is now no longer a distinct skillset, but a fixed part of the armamentarium of surgical options available. In every indication, the advantages of a minimally invasive approach include reduced intraoperative blood loss, less postoperative pain, and shorter rehabilitation times, as well as a marked reduction of overall and surgical postoperative morbidity. In the advent of modern oncologic treatment algorithms, these effects not only lower the immediate impact that an operation has on the patient, but also become important key steps in reducing the side-effects of surgery. Thus, they enable surgery to become a module in modern multi-disciplinary cancer treatment, which blends into multimodular treatment options at different times and prolongs and widens the possibilities available to cancer patients. In this quickly changing environment, the requirement to learn and refine not only open surgical but also different minimally invasive techniques on high levels deeply impact modern surgical training pathways. The use of modern elearning tools and new and praxis-based surgical training possibilities have been readily integrated into modern surgical education,which persists throughout the whole surgical career of modern gynecologic and visceral surgery specialists.

20. Social Media and Public Health: Opportunities and Challenges.

Author

Ahmed, Wasim, Vidal-Alaball, Josep, and Ahmed, Wasim

Subjects
Public health & preventive medicine, social media, disordered eating behaviours, body image, female, university students, telemedicine, carbon dioxide, air pollutants, vehicle emissions, primary care, machine learning, teleconsultation, remote consultation, classification, public health, short video, social network, TAM, cost analysis, health technology assessment, provider-to-provider telemedicine, telehealth, economic analysis, questionnaires and surveys, validation studies, health personnel, electronic nicotine delivery systems, smoking, twitter, poor doctor-patient relationship, healthcare consultation, mobile context, computer-mediated communication, point-of-care systems, ultrasonography, traffic-related pollution, primary health care, acceptability of health care, surveys and questionnaires, health communication, Spanish official medical colleges, stakeholders, Twitter, systemic lupus erythematosus (SLE), network analysis, topic modeling, text analysis, online media, vaccination, social marketing, stroke, prehospital emergency care, training, stroke code, large vessel occlusion, prehospital scales, hearing loss, latent topic, LDA, social Q&amp, A, public voice, public health emergency, policy evolution, product innovation, cooperative governance, COVID-19, coronavirus, masks, transmission
Abstract

Summary: Social media has the potential to provide rapid insights into unfolding public health emergencies such as infectious disease outbreaks. They can also be drawn upon for rapid, survey-based insights into various health topics. Social media has also been utilised by medical professionals for the purposes of sharing scholarly works, international collaboration, and engaging in policy debates. One benefit of using social media platforms to gain insight into health is that they have the ability to capture unfiltered public opinion in large volumes, avoiding the potential biases introduced by surveys or interviews. Social media platforms can also be utilised to pilot surveys, for instance, though the use of Twitter polls. Social media data have also been drawn upon in medical emergencies and crisis situations as a public health surveillance tool. A number of software and online tools also exist, developed specifically to aide public health research utilising social media data. In recent years, ethical issues regarding the retrieval and analysis of data have also arisen.

21. The 8th International Conference on Time Series and Forecasting.

Author

Rojas, Ignacio, Pomares, Hector, Valenzuela, Olga, Rojas, Fernando, Herrera, Luis, Kaufman, Peter, and Rojas, Ignacio

Subjects
Information technology industries, Computer science, readmission prediction, intensive care unit (ICU), recurrent neural network (RNN), longshort-term memory (LSTM), machine learning (ML), time series analysis, health forecasting, spectrum, utilization, prediction, time-series, clustering, K-Means, LSTM, CNN, outlier detection, outlier detection in time series, time series clustering, time series cluster evaluation, time series, anomaly detection, predictive maintenance, model evaluation, error diagnosis, convolutional neural network, all sky images, cloud-base height, machinelearning, : financial market volatility, VAR-DCC-GARCH, wavelet-based random forest, forecasting, synthetic data, shareable data, privacy, cross-correlation, DCCA method, oil derivatives, energy, accessibility, retainability, Markov chain, K-mean clustering, mobile data traffic, multivariate prediction, temporal, spatial, COVID-19, time series forecasting, NARNN, ARIMA, dynamic convergence, stationarity, unit root, ecosystem respiration, dynamic mode decomposition with control, time delay embedding, ordinal patterns, structural breaks, non-stationary time series, hydrological data, prediction intervals, seq2seq, oil production, automated machine learning, machine learning, time-series forecasting, PV systems, faults, diagnosis, signal processing, time series data
Abstract

Summary: The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields.

22. The Convergence of Human and Artificial Intelligence on Clinical Care - Part I.

Author

Abedi, Vida and Abedi, Vida

Subjects
Medicine, machine learning-enabled decision support system, improving diagnosis accuracy, Bayesian network, bariatric surgery, health-related quality of life, comorbidity, voice change, larynx cancer, machine learning, deep learning, voice pathology classification, imputation, electronic health records, EHR, laboratory measures, medical informatics, inflammatory bowel disease, C. difficile infection, osteoarthritis, complex diseases, healthcare, artificial intelligence, interpretable machine learning, explainable machine learning, septic shock, clinical decision support system, electronic health record, cerebrovascular disorders, stroke, SARS-CoV-2, COVID-19, cluster analysis, risk factors, ischemic stroke, outcome prediction, recurrent stroke, cardiac ultrasound, echocardiography, portable ultrasound, aneurysm surgery, temporary artery occlusion, clipping time, artificial neural network, digital imaging, monocytes, promonocytes and monoblasts, chronic myelomonocytic leukemia (CMML) and acute myeloid leukemia (AML) for acute monoblastic leukemia and acute monocytic leukemia, concordance between hematopathologists, mechanical ventilation, respiratory failure, ADHD, social media, Twitter, pharmacotherapy, stimulants, alpha-2-adrenergic agonists, non-stimulants, trust, passive adherence, human factors
Abstract

Summary: This edited book contains twelve studies, large and pilots, in five main categories: (i) adaptive imputation to increase the density of clinical data for improving downstream modeling; (ii) machine-learning-empowered diagnosis models; (iii) machine learning models for outcome prediction; (iv) innovative use of AI to improve our understanding of the public view; and (v) understanding of the attitude of providers in trusting insights from AI for complex cases. This collection is an excellent example of how technology can add value in healthcare settings and hints at some of the pressing challenges in the field. Artificial intelligence is gradually becoming a go-to technology in clinical care; therefore, it is important to work collaboratively and to shift from performance-driven outcomes to risk-sensitive model optimization, improved transparency, and better patient representation, to ensure more equitable healthcare for all.

23. The Digital Health in the Pandemic Era.

Author

Giansanti, Daniele and Giansanti, Daniele

Subjects
Medicine, Mental health services, n/a, digital contact tracing, IMMUNI app, COVID-19, students, digital care visit, online consultation, medical staff, healthcare personnel, user experience, magnetic resonance imaging (MRI), brain tumor, machine learning, digital health, e-health, pandemic, physical activity, performance evaluation, eHealth, self-care, chronic diseases, mental health, mindfulness, mobile health, social isolation, mental stress, feature selection, artificial intelligence, human health, lock down, normative activation model, COVID-19 prevention, prevention intention, IoT, obesity, classification, regression, real-time system, COVID-19 pandemic, contact tracing, CNN, chest X-ray images, hybrid learning, computer-aided diagnosis, remote psychotherapy, psychotherapy via telephone, psychotherapy via videoconferencing, tele-health, e-mental-health, psychotherapy, qualitative psychotherapy research, mixed-methods psychotherapy research, exergaming, breast neoplasms, physical function, telehealth, (d)health literacy, health literacy, health intervention, health strategy, medical data, medical imaging, data classification, image detection, YOLOv4, logistic regression, AI, deep learning, chatbot, health, health domain
Abstract

Summary: Digital health, virtual assistance, and telemedicine are terms often used interchangeably to refer to remote medical assistance, monitoring and care. Several studies and insights have developed these issues, analyzing the advantages and disadvantages and successes and failures and offering reflections on the implications and issues of these technologies in the health domain. The results of these investigations are affecting the redesign of hospital and outpatient management based on digital innovation using eHealth and mHealth. During the COVID-19 pandemic, this approach made it possible to offer assistance and continue care at home, protecting patients, preserving health workers, limiting the spread of the virus, and reducing the need for hospitalization. This reprint contains contributions dealing with the development of DH during the COVID-19 pandemic. The contributions are from various experts in different fields regarding the application of digital health, which, in some cases is also integrated with artificial intelligence, including digital contact tracing, mHealth, virtual reality, mental health, physiology, and rehabilitation.

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