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Surgical data science and artificial intelligence for surgical education
Thomas M Ward1, Pietro Mascagni2,3,4, Amin Madani5
1Department of Surgery, Surgical AI & Innovation Laboratory, Massachusetts General Hospital, Boston, Massachusetts.
Journal of Surgical Oncology
|July 10, 2021
Summary
Surgical data science (SDS) uses procedural data and artificial intelligence (AI) to enhance surgical care. This approach offers improved coaching, feedback, and decision support for surgical education and oncology.
Area of Science:
- Data science in healthcare
- Artificial intelligence in medicine
- Surgical informatics
Background:
- Surgical data science (SDS) focuses on improving healthcare quality and value.
- Procedural data capture, organization, analysis, and modeling are key components of SDS.
- Advancements in data capture and AI are driving new applications in surgery.
Purpose of the Study:
- To review major concepts in SDS and AI.
- To explore applications in surgical education.
- To examine applications in surgical oncology.
Main Methods:
- Literature review of SDS and AI concepts.
- Analysis of current trends in surgical data.
- Synthesis of AI applications in surgical contexts.
Main Results:
- SDS enables augmented and automated coaching, feedback, assessment, and decision support.
- AI integration in surgery is rapidly evolving.
- Significant potential exists for AI in surgical education and oncology.
Conclusions:
- SDS and AI integration are transforming surgical practice.
- Further research can optimize AI-driven surgical tools.
- The future of surgery involves data-driven insights and automation.
