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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: Medicine has evolved into a high level of specialization using the very detailed imaging of organs. This has impressively solved a multitude of acute health-related problems linked to single-organ diseases. Many diseases and pathophysiological processes, however, involve more than one organ. An organ-based approach is challenging when considering disease prevention and caring for elderly patients, or those with systemic chronic diseases or multiple co-morbidities. In addition, medical imaging provides more than a pretty picture. Much of the data are now revealed by quantitating algorithms with or without artificial intelligence. This Special Issue on "Systems Radiology and Personalized Medicine" includes reviews and original studies that show the strengths and weaknesses of structural and functional whole-body imaging for personalized medicine.

Summary: With the development of analytical instruments, the academic system has become more complicated, producing new journals one after another. Therefore, it became much important to clarify what is original of "Medicines". As the name Medicines indicates, it includes science and practice of caring for a patient and managing the diagnosis, prognosis, prevention, treatment or palliation of their injury or disease. Therefore, Medicines differs from other journals with similar title in that it covers a wide range of fields, from traditional medicine to rapidly developing molecular-targeted drugs, focusing on their pharmacological effects, structure-activity relationships, metabolic pathways, gene expression, using cultured cells, animals, and clinical trials. Most parts of this Special Issue were written by our editorial board members, who described the research topics and how they are engaged in their field of research. All of these articles are their life-long story. We collected a total number of 22 original works by basic researchers and clinical doctors. We hope that readers can get a chance to know the current status of diverse fields of medicines, and what your most important research themes are after reading these articles.

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: This reprint contains original research and review chapters concerning the latest advancements in various topics related to pediatric fractures. Topics include fractures of the face, clavicle, shoulder, elbow, forearm, wrist, pelvis, femur, and tibia; special considerations focus on osteogenesis imperfecta patients; and consideration is also given to general pediatric fracture topics, such as the influence of the COVID-19 pandemic, mortality after pediatric trauma, the effects of NSAID and electronic cigarette use, and chapters on epidemiology and physical activity.

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: The imperative to increase healthcare access, efficiency and effectiveness is nearly impossible to meet without reliance on technology. Telemedicine tools now include video, e-mail, text messaging, apps, and other mobile health modalities, deployed synchronously, asynchronously and in hybrid combinations to offer assessment, consultation, direct treatment, and integrated care. Within telemedicine, mental health is particularly well suited to technology platforms due to several inherent factors: provider shortages that are often more acute than in other specialties; the relatively reduced need for laboratory tests, imaging studies and physical examinations; the stigma still attached to mental illness; and diagnosis-specific obstacles that can complicate in person visits (e.g., pronounced fear in social anxiety disorder). The need to increase access, efficiency and effectiveness, combined with the relative ease of translating mental health interventions to technology-mediated delivery, have led researchers to explore various platforms, including: computerized cognitive behavioral therapy; online psychotherapy and online psychopharmacology; mobile therapy; virtual/augmented reality exposure therapy; serious games; and artificial intelligence. Yet, despite often positive efficacy data and an ever more technology-reliant lifestyle, the reach of telemental health remains relatively limited in comparison with its potential. We aim to capture the current status of digital and telecommunications technologies in mental health and the field's future trends and directions. Recently published data-as well as newly introduced platforms-have put both the promise and challenges of telemental health in sharp focus, making this an opportune time to compile a collection of high-quality, evidence-based and diverse articles that touch on various aspects of this technology revolution. This Research Topic collects articles that examine digital mental health interventions across different platforms and modes of delivery. The scope is broad to reflect the richness of the field and the many questions it raises: standalone vs. supported models; comparisons with "traditional" modalities; psychotherapeutic vs. psychopharmacological interventions; efficacy; patient attrition; cost-effectiveness; ethical issues; and insurer and malpractice coverage.

Summary: The "Creating Age-friendly Communities: Housing and Technology" 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.

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: Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has spread worldwide from the beginning of 2020. The infection is mostly asymptomatic but some patients may develop COVID‑19 (coronavirus disease 2019) with a severe or critical course leading to pneumonia, acute respiratory distress syndrome, and multiorgan failure. Apart from the virus‑related damage of the lungs, pathomechanism of the disease seems to be linked to thromboembolism and inflammation accompanied by overproduction of proinflammatory cytokines, termed a cytokine storm, responsible for multiorgan damage and death. Since the development of a new therapeutic molecule, dedicated strictly to a particular virus is time‑consuming, physicians and scientists have started to test and repurpose old medications. Unfortunately, after one year of pandemics, there is still a lack of optimal therapy and no clear indicators of recovery. A major issue is also insufficient knowledge on predictors of the severe or deadly course of the disease, which could also help to switch from one therapeutic option to another. Due to many gaps still existing in the management of COVID-19, there is a need for the accumulation of new data particularly from real-world experience, which could be applicable to practice guidelines. The objective of this special issue of the Journal of Clinical Medicine is to provide an update on the mangement for the diagnostic workup and pharmacotherapy of SARS‑CoV‑2 infection.

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: 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.