Artificial intelligence (AI) and machine learning (ML) are comparatively new fields and only recently have efforts begun to develop applications of these models to surgical practice and education. AI and ML models may be useful tools in predicting surgical risk to reduce unnecessary interventions for low-risk patients and in stratifying high-impact interventions for high-risk patients. Most surgeons, however, have not had the opportunity to learn about AI and ML, lack basic knowledge of these data-driven processes and systems, and are unaware of their potential applications in surgical practice.
This introductory course from the ACS Division of Education highlights the essential principles of AI and ML and their application to support decision-making and enhance surgical care. Participants will develop the foundational knowledge of the principles on which AI and ML are structured and may be able to identify opportunities for possible application of the technologies to their practices. With further development, data-driven machine intelligence most likely will be able to inform clinical decision-making and allow surgeons to more accurately assess risk, predict disease progression, and manage patients with early stages of disease.
Specific examples and algorithms illustrated in this course include
- Predicting the risk of small bowel obstruction during a specified period of time after a procedure
- Enhancing the diagnosis and malignancy prediction of indeterminate thyroid nodules
- Improving the diagnosis and management of patients in the earliest stage of breast cancer
Limitations and ethical considerations of ML in practice are also presented. This course should assist surgeons and leaders in surgery departments with developing some fluency in the principles and language of AI and ML to facilitate conversations between leadership and technical experts.
Course Modules
The course includes the following eight online modules:
- Course Introduction
- Using Machine Learning in the Service of our Patients
- Using Machine Learning in the Diagnosis and Treatment of Small Bowel Obstruction
- Using Machine Learning for the Prediction of Malignancy in Thyroid Nodules
- Using Machine Learning to Diagnose Mammographically Detected Breast Cancer
- What Value does AI Bring in the Surgical Profession?
- Automated Analysis of Surgical Video
- Explainable AI for Improving Surgical Performance and Safety
- Ethical Considerations for Machine Learning
- Conclusion: The Future of Machine Learning for Surgeons
Contact Information
Please direct questions to pblair@facs.org.
