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.
By:
Daniel A. Hashimoto,
Guy Rosman,
Ozanan R. Meireles
Imprint: McGraw-Hill Education
Country of Publication: United States [Currently unable to ship to USA: see Shipping Info]
Dimensions:
Height: 241mm,
Width: 196mm,
Spine: 25mm
Weight: 1.037kg
ISBN: 9781260452730
ISBN 10: 1260452735
Pages: 432
Publication Date: 15 September 2021
Audience:
General/trade
,
ELT Advanced
Format: Paperback
Publisher's Status: Active
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
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.
