Main description:

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.

Contents:

1. History, Big Data and Artificial Intelligence in Medicine: Past, Present, and Future 2. Artificial Intelligence in Primary Care and Preventive Medicine 3. Artificial Intelligence in General Internal Medicine 4. Artificial Intelligence in Radiology 5. Artificial Intelligence in Pathology 6. Artificial Intelligence in Infectious Disease 7. Artificial Intelligence in Gastroenterology 8. Artificial Intelligence in Cardiology 9. Artificial Intelligence in Hematology and oncology 10. Artificial intelligence in Dermatology 11. Artificial Intelligence in Ophthalmology 12. Artificial Intelligence in Mental health 13. Artificial Intelligence in Neurology 14. Artificial Intelligence in Pulmonary and Critical care 15. Artificial intelligence in Rheumatology 16. Artificial intelligence in Surgery 17. Artificial intelligence in OB-GYN 18. Current Challenges 19. Future Directions