Stemming from environmental, genetic, and situational factors, chronic disease is a critical concern in modern medicine. Managing treatment and controlling symptoms is imperative to the longevity and quality of life of patients with such diseases. The Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions features current research on the diagnosis, monitoring, management, and treatment of recurring diseases such as diabetes, Parkinson's disease, autoimmune disorders, and others. This handbook is intended for practitioners and researchers across various disciplines including, but not limited to, biology, biomedical engineering, computer science, and information and communication technologies. Aimed at identifying new disease determinants and the way in which new technologies can contribute to improved health outcomes, this handbook covers a variety of topics, including wearable and mobile technologies, capillaroscopy imaging, diagnostic and monitoring methods, and disease prediction modeling, among others.

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

This book focuses on optimizing management and outcomes rather than on routine diagnosis of chronic disease. The reader learns proven methods for treating the most common chronic conditions that they see in daily practice. Chapters are structured to help physicians adopt evidence-based management techniques specific for each condition. Special emphasis is placed on the use of action plans and educational resources for promoting patient self-management.

Stemming from environmental, genetic, and situational factors, chronic disease is a critical concern in modern medicine. Managing treatment and controlling symptoms is imperative to the longevity and quality of life of patients with such diseases. Chronic Illness and Long-Term Care: Breakthroughs in Research and Practice features current research on the diagnosis, monitoring, management, and treatment of chronic diseases such as diabetes, Parkinson's disease, autoimmune disorders, and many more. Highlighting a range of topics such as medication management, quality-of-life issues, and sustainable health, this publication is an ideal reference source for hospital administrators, healthcare professionals, academicians, researchers, and graduate-level students interested in the latest research on chronic diseases and long-term care.

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.