Artificial Intelligence in Clinical Practice

Artificial Intelligence in Clinical Practice: How AI Technologies Impact Medical Research and Clinics compiles the current research on Artificial Intelligence within each medical subspecialty for use as a reference to assist with diagnosis, clinical decision making, disease prediction and prevention, and the facilitation of precision medicine. It defines the basic concepts of big data and AI in medicine, and highlights the current applications, challenges, ethical issues, and biases associated with the implementation of AI in medicine. Each chapter discusses AI applied to a specific medical subspecialty: primary care and preventive medicine; general internal medicine; radiology; pathology; infectious disease; gastroenterology; cardiology; hematology; oncology; dermatology; ophthalmology; mental health; neurology; pulmonary and critical care; rheumatology; surgery; and OB-GYN. It is a valuable resource for clinicians, students, researchers and members of medical and biomedical fields who are interested to learn more about artificial intelligence technologies applied to medicine. Provides history and overview of the various modalities of AI and their applications within each field of medicine as narrated by leading experts Discusses current AI-based medical research including landmark trials within each field of medicine Addresses the current knowledge gaps that clinicians commonly face, which prevent the application of AI-based research to clinical practice Encompasses examples of specific cases, and discusses challenges and biases associated with AI