AI in Clinical Practice: A Guide to Artificial Intelligence and Digital Medicine

ISBN-13: 9780443140549 / Angielski

Giampaolo Collecchia; Riccardo de Gobbi

Opis

AI in Clinical Practice: A Guide to Artificial Intelligence and Digital Medicine explains how artificial intelligence is applied to medicine, illustrating not only its enormous potential but also ancillary issues and the limits and risks inherent in its use on a large scale. The book focuses on the intersection between medicine and AI and its implications on the impact of human health care delivery. Topics discussed  include wearable devices, health data, Internet of Things, virtual reality, robotic assistance system, and digital intelligence in the health sector. Additionally, sections discuss diagnostics and decision-making systems and machine/deep learning in clinical setting. This is a valuable resource for clinicians, researchers, students and members of the biomedical and medical fields who want to learn more about the use of AI to improve patient care.

Spis treści

Section 1: ARTIFICIAL INTELLIGENCE: "WHAT ARE WE TALKING ABOUT " 1. Glossary 2. What is meant by AI: knowing it in order to use it in the best way 3. How AI works: machine learning, deep learning, neural networks, black boxes 4. The limits of the algorithms, or the data is (not) "given"

Section 2: THE WORLD OF SENSORS 5. The datanami (tsunami of data): or when the data is perhaps too much 6. Wearable devices and the Internet of Things 7. The sentry watch

Section 3: DIGITAL INTELLIGENCE AND HEALTH 8. Diagnostics and decision-making systems: Applications in radiology, oncology, pathology, dermatology, ophthalmology, cardiology, gastroenterology, neurology, genetics, at the health system level 9. Applications in the psychological-psychiatric field 10. From personalized medicine to precision medicine 11. The search for new drugs and digital therapies 12. Virtual reality: great therapeutic potential and possible risks 13. Chance or Chaos14. The robotic assistance system 15. Digital medications/Therapy 16. Will "Amplifying technology" really expand our knowledge? 17. Diagnosis by images18. Machine Learning and Deep Learning 19. At the end of the journey.final reflections