"This is the first book-length account of early efforts to computerize medical diagnosis. It explores how these efforts produced and interacted with certain professional tensions, disease constructions, personal identities, cultural ideals, economic interests, and material practices. The book offers a historical account that raises pressing questions, problems, and challenges that must be addressed as we work to harness artificial intelligence for the benefit of the medical profession and its patients"--

This book gathers selected papers that were submitted to the 2021 International Conference on Digital Science (DSIC 2021) that aims to make available the discussion and the publication of papers on all aspects of single and multidisciplinary research on conference topics. DSIC 2021 was held on October 15–17, 2021. An important characteristic feature of conference is the short publication time and worldwide distribution. Written by respected researchers, the book covers a range of innovative topics related to: digital economics; digital education; digital engineering; digital environmental sciences; digital finance, business and banking; digital health care, hospitals and rehabilitation; digital media; digital medicine, pharma and public health; digital public administration; digital technology and applied sciences. This book may be used for private and professional non-commercial research and classroom use (e.g., sharing the contribution by mail or in hard copy form with research colleagues for their professional non-commercial research and classroom use); for use in presentations or handouts for any level students, researchers, etc.; for the further development of authors’ scientific career (e.g., by citing, and attaching contributions to job or grant application).

This anthology for Medical Sociology courses, is edited by two leading experts in the field. It brings together readings from the scholarly literature on health, medicine, and health care, covering some of the most timely health issues of our day, including eating disorders, the effects of inequality on health, how race, class, and gender affect health outcomes, the health politics of asthma, the effects of health care reform, the pharmaceutical industry, health information on the Internet, and the impacts of the COVID-19 pandemic.

Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

In the medical field, there is a constant need to improve professionals’ abilities to provide prompt and accurate diagnoses. The use of image and pattern recognizing software may provide support to medical professionals and enhance their abilities to properly identify medical issues. Medical Image Processing for Improved Clinical Diagnosis provides emerging research exploring the theoretical and practical aspects of computer-based imaging and applications within healthcare and medicine. Featuring coverage on a broad range of topics such as biomedical imaging, pattern recognition, and medical diagnosis, this book is ideally designed for medical practitioners, students, researchers, and others in the medical and engineering fields seeking current research on the use of images to enhance the accuracy of medical prognosis.

When it comes to Parkinson's disease, one of the most important issues revolves around early detection and accurate diagnosis. The intricacies of this neurodegenerative disorder often elude timely identification, leaving patients and healthcare providers grappling with its progressive symptoms. Ethical concerns surrounding the use of machine learning to aid in diagnosis further complicate this challenge. This issue is particularly significant for research scholars, PhD fellows, post-doc fellows, and medical and biomedical scholars seeking to unravel the mysteries of Parkinson's disease and develop more effective treatments. Intelligent Technologies and Parkinson’s Disease: Prediction and Diagnosis serves as a beacon of hope in the quest to revolutionize Parkinson's disease diagnosis and treatment. It unveils the remarkable potential of artificial intelligence (AI) and machine learning (ML) in remodeling the way we approach this debilitating condition. With a comprehensive exploration of AI's capacity to analyze speech patterns, brain imaging data, and gait patterns, this book offers a powerful solution to the challenges of early detection and accurate diagnosis.

Medical care is the most critical issue of our time and will be so for the foreseeable future. In this regard, the pace and sophistication of advances in medicine in the past two decades have been truly breathtaking. This has necessitated a growing need for comprehensive reference resources that highlight current issues in specific sectors of medicine. Keeping this in mind, each volume in the Current Issues in Medicine series is a stand‐alone text that provides a broad survey of various important topics in a focused area of medicine—all accomplished in a user-friendly yet interconnected format. This volume addresses advances in medical imaging, detection, and diagnostic technologies. Technological innovations in these sectors of medicine continue to provide for safer, more accurate, and faster diagnosis for patients. This translates into superior prognosis and better patient compliance, while reducing morbidity and mortality. Hence, it is imperative that practitioners stay current with these latest advances to provide the best care for nursing and clinical practices. While recognizing how expansive and multifaceted these areas of medicine are, Advances in Medical Imaging, Detection, and Diagnosis addresses crucial recent progress, integrating the knowledge and experience of experts from academia and the clinic. The multidisciplinary approach reflected makes this volume a valuable reference resource for medical practitioners, medical students, nurses, fellows, residents, undergraduate and graduate students, educators, venture capitalists, policymakers, and biomedical researchers. A wide audience will benefit from having this volume on their bookshelf: health care systems, the pharmaceutical industry, academia, and government.