Build a solid foundation in surgical AI with this engaging, comprehensive guide for AI novices

Machine learning, neural networks, and computer vision in surgical education, practice, and research will soon be de rigueur. Written for surgeons without a background in math or computer science, Artificial Intelligence in Surgery provides everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice.

Comprehensive and easy to understand, this first-of-its-kind resource illustrates the use of AI in surgery through real-life examples. It covers the issues most relevant to your practice, including:

Neural Networks and Deep LearningNatural Language ProcessingComputer VisionSurgical Education and SimulationPreoperative Risk StratificationIntraoperative Video AnalysisOR Black Box and Tracking of Intraoperative EventsArtificial Intelligence and Robotic SurgeryNatural Language Processing for Clinical DocumentationLeveraging Artificial Intelligence in the EMREthical Implications of Artificial Intelligence in SurgeryArtificial Intelligence and Health PolicyAssessing Strengths and Weaknesses of Artificial Intelligence Research

Finally, the appendix includes a detailed glossary of terms and important learning resources and techniques―all of which helps you interpret claims made by studies or companies using AI.

 

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