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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.

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.

Summary: This reprint brings together fifteen articles published in the Special Issue of the journal Atmosphere, entitled "High-Performance Computing Serving Atmospheric Transport & Dispersion Modelling". These articles cover a wide variety of topics related to air quality in urban areas and nature-based solutions to improve it in the context of climate change; impact studies on human health and the environment of facilities and infrastructure projects as well as risk studies; the assessment of emerging threats; and preparations for and responses to emergencies involving toxic, flammable, or explosive atmospheric releases. As the fifteen articles presented here remarkably illustrate, what these contemporary topics have in common is the implementation of multi-scale simulations of atmospheric transport and dispersion by means of physical models of computational fluid dynamics (CFDs), whose potential is enhanced by high-performance computing (HPC). This reprint thus addresses the answers provided by modelling and the most advanced simulations to some societal matters of major interest.

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.

Summary: This book collects recent research in the field of care for neurodevelopmental disorders, emphasizing transdisciplinary work in clinical, educational and family contexts. It presents an opportunity to learn about the impact of participation on children and adolescents with neurodevelopmental disorders. Mainly, new therapeutic approaches are presented in children and adolescents with autism spectrum disorder, attention-deficit/hyperactivity disorder, or motor coordination disorders.

Summary: Carpal tunnel syndrome (CTS) is a very common median nerve compression neuropathy at wrist level. It causes unplesant symptoms to patient as well as a financial burden for society. Conservative treatment helps with mild and transient symptoms, but often this syndrome requires surgical treatment. Surgical decompression of the median nerve is one of the most common surgical operations. If the symptom persists for a long time and treatment is delayed, this can result in a lack of sensation in the median area in addition to thenar atrophy and weakness of the thumb opposition. There are many impressive things behind CTS that we do not know yet; anatomical causes, links to other diseases and medication, occupational exposures and predisposing lifestyle risk factors. Diagnostics and differential diagnostics of CTS have their own challenges. Conservative treatment practices of CTS are diverse and unambiguous best practice is not clear. Clinical symptoms, electromyography (EMG) finding, and possible differential diagnostic challenges should be considered when deciding on surgery. Surgical treatment varies somewhat from hospital to hospital and from country to country. When the CTS diagnosis and treatment is done too late for nerves to recover or there is perioperative complication, some late reconstructive surgeries might be needed. These nerve surgery techniques can be done by experienced hand surgeons. The quality of care, complications, and cost effectiveness of different methods require further research. This Special Issue will present the latest research on this interesting and clinically significant syndrome.

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.

Summary: Personalised medicine is the next step in healthcare, especially when applied to genetically diverse diseases such as cancers. Naturally, a host of methods need to evolve alongside this, in order to allow the practice and implementation of individual treatment regimens. One of the major tasks for the development of personalised treatment of cancer is the identification and validation of a comprehensive, robust, and reliable panel of biomarkers that guide the clinicians to provide the best treatment to patients. This is indeed important with regards to radiotherapy; not only do biomarkers allow for the assessment of treatability, tumour response, and the radiosensitivity of healthy tissue of the treated patient. Furthermore, biomarkers should allow for the evaluation of the risks of developing adverse late effects as a result of radiotherapy such as second cancers and non-cancer effects, for example cardiovascular injury and cataract formation. Knowledge of all of these factors would allow for the development of a tailored radiation therapy regime. This Special Issue of the Journal of Personalised Medicine covers the topic of Radiation Response Biomarkers in the context of individualised cancer treatments, and offers an insight into some of the further evolution of radiation response biomarkers, their usefulness in guiding clinicians, and their application in radiation therapy.

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.

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.

Summary: This book presents some of the latest available information on automated ECG analysis written by many of the leading researchers in the field. It contains a historical introduction, an outline of the latest international standards for signal processing and communications and then an exciting variety of studies on electrophysiological modelling, ECG Imaging, artificial intelligence applied to resting and ambulatory ECGs, body surface mapping, big data in ECG based prediction, enhanced reliability of patient monitoring, and atrial abnormalities on the ECG. It provides an extremely valuable contribution to the field.

Summary: Progress in information technology has fostered a global explosion of data generation. Accumulated big data are now estimated to be 4.4 zettabytes in the digital universe; and trends predict an exponential increase in the future. Health data are gathered from professional routine care and other expanded sources including the social determinants of health, such as Internet of Things. Biomedical research has recently moved through three stages in digital healthcare: (1) data collection; (2) data sharing; and (3) data analytics. With the explosion of stored health data, dental medicine is edging into its fourth stage of digitization using new technologies including augmented and virtual reality, artificial intelligence, and blockchain. Big data collaborations involve interactions between a diverse range of stakeholders with analytical, technical and political focus. In oral healthcare, data technology has many areas of application: prognostic analysis and predictive modeling, the identification of unknown correlations of diseases, clinical decision support for novel treatment concepts, public health surveys and population-based clinical research, as well as the evaluation of healthcare systems. The objective of this Special Issue is to provide an update on the current knowledge with state-of-the-art theory and practical information on human and social perspectives that determine the uptake of technological innovations in big data science in the field of dental medicine. Moreover, it will focus on the identification of future research needs to manage the continuous increase in health data and to accomplish its clinical translation for patient-centered research and personalized dentistry. This Special Issue welcomes all types of studies and reviews considering the perspectives of different stakeholders on technological innovations for big data science in all dental disciplines. Kind regards,

Summary: In recent years, artificial intelligence has increasingly been playing an essential role in diverse areas in medicine, assisting clinicians in patient management. In nephrology and transplantation, artificial intelligence can be utilized to enhance clinical care, such as through hemodialysis prescriptions and the follow-up of kidney transplant patients. Furthermore, there are rapidly expanding applications and validations of comprehensive, computerized medical records and related databases, including national registries, health insurance, and drug prescriptions. For this Special Issue, we made a call to action to stimulate researchers and clinicians to submit their invaluable works and present, here, a collection of articles covering original clinical research (single- or multi-center), database studies from registries, meta-analyses, and artificial intelligence research in nephrology including acute kidney injury, electrolytes and acid-base, chronic kidney disease, glomerular disease, dialysis, and transplantation that will provide additional knowledge and skills in the field of nephrology and transplantation toward improving patient outcomes.

Summary: When the domestic government, the private sector, and people in various professional fields talk about long-term care issues, they all focus on creating a warm and home-like care institution. However, we actively emphasize the importance of community-based long-term care. For "aging in place", the development of domestic non-institutional care is still in its infancy, and some long-term care needs must still be met through institutional care, and the facilitation of the extension or outreach of community-based care and respite service platforms for the development of community-based long-term care still rely on institutional care. The history of the development of long-term care in Taiwan is much shorter than that of Japan, Europe, the United States, and Canada. Despite years of hard work and rapid development, the long-term care resources needed to establish a complete system in terms of universalization, fairness, accessibility, and selectivity are not available. In the future, based on the soundness of institutional care, it hoped that outreach will move toward the goals of community care and aging in place. We hope the studies in this Special Issue will help further develop clinical medicine for healthcare and stainability.

Summary: This Special Issue focuses on the current state of pharmacogenomics (PGx) and the extensive translational process, including the identification of functionally important PGx variation; the characterization of PGx haplotypes and metabolizer statuses, their clinical interpretation, clinical decision support, and the incorporation of PGx into clinical care.

Summary: The issue of Cancers Journal entitled "Role of Medical Imaging in Cancers" presents a detailed summary of evidences about molecular imaging, including the role of computed tomography (CT), magnetic resonance imaging (MRI), single photon emission tomography (SPET) and positron emission tomography (PET) or PET/CT or PET/MR imaging in many type of tumors (i.e. sarcoma, prostate, breast and others), motivating the role of these imaging modalities in different setting of disease and showing the recent developments, in terms of radiopharmaceuticals, software and artificial intelligence in this field. The collection of articles is very useful for many specialists, because it has been conceived for a multidisciplinary point of view, in order to drive to a personalized medicine.

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.