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Intraoperative Gastroscopy for Tumor Localization in Laparoscopic Surgery for Gastric Adenocarcinoma
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ChatGPT's Gastrointestinal Tumor Board Tango: A limping dance partner?
Ughur Aghamaliyev1, Javad Karimbayli2, Clemens Giessen-Jung3
1Department of General, Visceral and Transplantation Surgery, LMU University Hospital, LMU Munich, Germany.
European Journal of Cancer (Oxford, England : 1990)
|May 10, 2024
Summary
ChatGPT 3.5 shows promise in aligning general treatment strategies for gastrointestinal tumors with multidisciplinary tumor boards (MTBs). However, it struggles with precise chemotherapy and follow-up recommendations, limiting its direct clinical application.
Area of Science:
- Oncology
- Artificial Intelligence in Medicine
- Clinical Decision Support
Background:
- Multidisciplinary tumor boards (MTBs) are crucial for complex cancer case management.
- AI tools like ChatGPT 3.5 are increasingly explored for clinical applications.
- Assessing AI's reliability in oncology treatment recommendations is essential.
Purpose of the Study:
- To evaluate ChatGPT 3.5's consistency and replicability in gastrointestinal tumor treatment recommendations.
- To compare AI-generated plans against MTB decisions.
- To assess the precision of AI in specific treatment details like chemotherapy and follow-up.
Main Methods:
- Retrospective analysis of 115 gastrointestinal malignancy cases from 448 MTB reviews.
- ChatGPT 3.5 generated treatment recommendations based on patient data.
- Oncology fellows evaluated AI recommendations against MTB decisions.
Main Results:
- ChatGPT 3.5 provided case-specific recommendations in 81% of cases.
- Overall treatment strategy concordance was 83% for case-specific responses.
- Exact treatment concordance, especially for chemotherapy regimens, was lower (65%).
Conclusions:
- ChatGPT 3.5 aligns with general treatment strategies but lacks precision in specific plans.
- Chemotherapy regimens and follow-up protocols present significant challenges for AI accuracy.
- Caution is advised for direct clinical decision-making using ChatGPT 3.5 in MTBs.
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