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Current applications of artificial intelligence for intraoperative decision support in surgery
Allison J Navarrete-Welton1, Daniel A Hashimoto2,3
1Surgical Artificial Intelligence and Innovation Laboratory, Massachusetts General Hospital, Boston, MA, 02114, USA.
Frontiers of Medicine
|July 5, 2020
Summary
Artificial intelligence (AI) offers promising surgical decision support by augmenting information and accelerating pathology. However, methodological limitations hinder assessing the clinical impact of current AI applications in surgery.
Area of Science:
- Medical Artificial Intelligence (AI)
- Surgical Technology
- Clinical Decision Support Systems
Background:
- Medical AI research has advanced significantly, with notable progress in surgical applications.
- AI-based decision support systems are increasingly explored for the intraoperative phase of surgery.
Purpose of the Study:
- To conduct a scoping review of AI-based decision support systems for the intraoperative surgical phase.
- To identify technological approaches, motivations, and limitations in this field.
Main Methods:
- Systematic literature search and review of 21 relevant research papers.
- Categorization of AI system motivations and analysis of methodological approaches.
Main Results:
- Identified three primary motivations: augmenting surgeon information, accelerating intraoperative pathology, and recommending surgical steps.
- Observed a wide range of technologies across multiple surgical specialties.
- Noted significant methodological shortcomings in most studies, impeding clinical significance assessment.
Conclusions:
- AI holds considerable promise for improving surgical care and patient outcomes.
- Future research should address methodological limitations to better evaluate AI's clinical impact.
- Opportunities exist for collaboration between AI researchers and clinicians to advance surgical decision support.
