Search

Your search keyword 'LN cat08778a' showing total 23 results
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, José A. and Orosa, José 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, Przemysław, 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, Tāmaki 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.

Catalog

Books, media, physical & digital resources
See catalog results