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The first surgical AI guide of its kind! Machine learning, neural networks, and computer vision for surgical education, practice, and research

While radiology and pathology are on the leading edge of AI in healthcare, surgery is showing tremendous potential for disruption by AI. Written for anyone not steeped in mathematics, technology, or engineering, this matchless guide gets ahead of the knowledge curve now-so you can evaluate new technologies with a critical eye and make informed decisions about bringing AI into your practice.

Artificial Intelligence in Surgery covers the history, principles, and main subfields of AI, offering examples of current and near-future use cases for AI in surgery. It gives you a clear understanding of the ethical implications of AI, its potential impact on healthcare policy, and how to read and interpret papers that use AI. The appendix includes a quick reference on AI techniques, their use cases, strengths, and limitations; glossary of terms; important learning resources; and techniques (including examples of appropriate use cases, advantages, and limitations)-all of which can be used to interpret claims made by studies or companies using AI.

Contents:

1. A Brief History of Artificial Intelligence - Maria S. Alteiri, Cara B. Jones, and Guy Rosman
2. Large Databases in Surgery - Sanford E. Roberts and Rachel R. Kelz
3. Machine Learning for Medicine - Frank Rudzicz
4. Neural Networks and Deep Learning - Deepak Alapatt, Pietro Mascagni, Vinkle Srivastav, and Nicolas Padoy
5. Natural Language Processing - Leo Anthony Celi, Daniel Gruhl, Euma Ishii, Chaitanya Shivade, Joseph Terdiman, and Joy Tzung-yu Wu
6. Computer Vision in Surgery: Fundamental Principles and Applications - Daniel A. Hashimoto, Amin Madani, Allison Navarrete-Welton, and Guy Rosman
7. Artificial Intelligence for Surgical Education and Intraoperative Analysis - Babak Namazi, Venkat Devarajan, and Ganesh Sankaranarayanan
8. Automated Surgical Coaching for Individual Improvement - Anand Malpani
9. Preoperative Risk Stratification - Majed W. El Hechi, Samer A. Nour Eddine, and Haytham M.A. Kaafarani 10. The OR Black Box System - Marc Levin, Mitchell G. Goldenberg, and Teodor P. Grantcharov
11. Applications of Deep Learning in Surgery - Quanzheng Li
12. Artificial Intelligence in Robotic Surgery - Daniel Naftalovich, Camille Stewart, Joel Burdick, and Yuman Fong
13. Natural Language Processing and Artificial Intelligence for Clinical Documentation - David Y. Ting
14. Ethics of Artificial Intelligence in Surgery - Frank Rudzicz and Raeid Saqur
15. Policy Implications of Artificial Intelligence in Surgery - Benjamin H. Jacobson, Megan B. Diamond, and Winta T. Mehtsun
16. Practical Considerations in Utilization of Computer Vision - Thomas Ward
17. Assessment of Artificial Intelligence Research in Surgery - Daniel A. Hashimoto
18. Automation and the Future of Surgery - Ozanan R. Meireles, Daniela Rus, and Daniel A. Hashimoto

Appendices
Appendix I - Glossary
Appendix II - Resources for Additional Education in Artificial Intelligence