Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice / Edition 1

by Ozanan R. Meireles, Guy Rosman, Daniel A. Hashimoto

Overview

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 Learning
• Natural Language Processing
• Computer Vision
• Surgical Education and Simulation
• Preoperative Risk Stratification
• Intraoperative Video Analysis
• OR Black Box and Tracking of Intraoperative Events
• Artificial Intelligence and Robotic Surgery
• Natural Language Processing for Clinical Documentation
• Leveraging Artificial Intelligence in the EMR
• Ethical Implications of Artificial Intelligence in Surgery
• Artificial Intelligence and Health Policy
• Assessing 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.

Product Details

ISBN-13:	9781260452730
Publisher:	McGraw Hill LLC
Publication date:	07/01/2021
Pages:	432
Product dimensions:	7.30(w) x 9.30(h) x 1.00(d)

About the Author

Daniel A. Hashimoto, MD, MS, is the Associate Director of Research at the Surgical Artificial Intelligence & Innovation Laboratory at the Massachusetts General Hospital. He is co-chair of the Artificial Intelligence Task Force for the Society of American Gastrointestinal and Endoscopic Surgeons and has published in the New England Journal of Medicine, Nature Biotechnology, and Annals of Surgery, amongst others.

Guy Rosman, PhD, is the Associate Director of Engineering at the Surgical Artificial Intelligence & Innovation Laboratory and senior research scientist at the Toyota Research Institute, where he works on inference topics related to autonomous driving.

Ozanan R. Meireles, MD, FACS, is the Director of the Surgical Artificial Intelligence & Innovation Laboratory and Assistant Professor of Surgery at Massachusetts General Hospital and Harvard Medical School.

Table of 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

Editorial Reviews

Reviewer: Carol Scott-Conner, MD, PhD, MBA, MFA (University of Iowa Hospitals and Clinics)
Description: This is a concise but comprehensive introduction to artificial intelligence (AI) and its applications to surgery. Chapters are illustrated with relevant photographs, diagrams, and algorithms.
Purpose: As stated in the book, "The overall objective of this book is to provide an approachable resource on AI to those in surgery who do not necessarily have a technical background..." The back cover further states that it will provide "everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice." These are worthy objectives, and the book is largely successful in meeting them. Links are provided for actual immersive experiences, for example, a "Hands-On Deep Learning Lab" accessible by following a link (or scanning a QR code included in the book). There is mathematics in some chapters, for those who wish to delve more deeply, but the bulk of the material can readily be understood without the math.
Audience: The audience is surgeons of all levels from trainee to practitioner. It amply meets the needs of its intended audience. The authors are highly credible authorities in the field.
Features: The book begins, appropriately, with a brief history of the field. A valuable chapter on large databases in surgery follows, and then the book delves into machine learning and natural language processing, and computer vision. The bulk of the book is devoted to applications of these aspects of AI to surgical training, coaching, and practice. Robotics is included, and there are nice chapters on ethics and policy implications. There are no obvious shortcomings, but doubtless rapid advances in the field will justify a new edition in the coming years.
Assessment: This is an attractive, well-written, comprehensive introduction to a complex topic. It will fill a unique niche in the field and be of value to researchers, clinicians, and trainees. Non-physicians (i.e., engineers) may also find it of value.

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