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Clinical Desire for an Artificial Intelligence-Based Surgical Assistant System: Electronic Survey-Based Study.
Soo Jin Park1, Eun Ji Lee1, Se Ik Kim1
1Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Republic of Korea.
JMIR Medical Informatics
|May 16, 2020
Summary
Surgeons desire AI-based surgical assistants to improve laparoscopic surgery, citing issues with human assistant skillfulness and camera control. This AI system could replace a significant portion of the surgical workforce, with high interest in its adoption.
Area of Science:
- Surgical Technology
- Artificial Intelligence in Medicine
- Medical Robotics
Background:
- Artificial intelligence (AI) is increasingly used in medical research, particularly in operating rooms.
- Current AI applications in surgery are limited, often to software or small tasks.
- AI-based solo surgery (AISS) is conceptualized as a single surgeon performing laparoscopic surgery with AI assistance.
Purpose of the Study:
- To evaluate surgeon experiences with conventional laparoscopic surgery.
- To identify limitations of current laparoscopic surgical systems.
- To assess surgeon desire for an AI-based surgical assistant system for AISS.
Main Methods:
- An online survey was conducted among gynecologists, urologists, and general surgeons.
- The survey included questions on surgical experience, system limitations, and desire for AI assistance.
- Data were collected from June to August 2017.
Main Results:
- Most surgeons require multiple assistants, with skillfulness being crucial.
- Unskilled camera and instrument movements were major discomforts.
- A significant portion of surgeons (39.1%) believe AI could replace 41%-60% of staff, with 83.3% willing to purchase the system.
Conclusions:
- Surgeons experience discomfort with current laparoscopic systems due to assistant skill limitations.
- There is a strong desire for AI-based surgical assistant systems to enhance safety and comfort.
- AI-assisted surgery offers a potential solution to improve efficiency and address workforce needs.
