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Artificial Intelligence Language Models in Oncology: A Cross-Sectional Analysis of Published Studies
Nandi Edwards1, Samy Kannout1, Daniel Zhang2
1Temerty Faculty of Medicine, University of Toronto, Toronto, CAN.
Cureus
|May 15, 2026
Summary
Research on ChatGPT in oncology is rapidly expanding, focusing on diagnostic accuracy and performance evaluations. Current studies concentrate on general and radiation oncology, with limited exploration in medical and basic sciences.
Area of Science:
- Oncology
- Artificial Intelligence
- Medical Informatics
Background:
- ChatGPT's rapid emergence in November 2022 has spurred extensive evaluation across medical fields, including oncology.
- The specific characteristics and clinical focus of these oncology-related evaluations are not well-defined.
Purpose of the Study:
- To characterize the scope, methodological approaches, and clinical focus of oncology-specific studies evaluating ChatGPT.
- To provide a structured overview of the current research landscape concerning ChatGPT in oncology.
Main Methods:
- A descriptive, cross-sectional meta-research analysis of oncology-related studies evaluating ChatGPT.
- Studies were identified from Ovid Medline and Embase up to December 25, 2025.
- Included studies were categorized by design, oncology discipline, and AI task.
Main Results:
- 1,325 oncology-related studies evaluating ChatGPT were identified, with a significant increase in publications from 2023 to 2025.
- Most studies were clinical (72%), focusing on methodological or performance evaluations (69%).
- Research concentrated on general/multidisciplinary (53%) and radiation oncology (43%), with limited studies in medical (2%) and basic sciences (2%). Diagnostic accuracy/classification tasks were most common (57%).
Conclusions:
- Oncology research on ChatGPT predominantly uses methodological and performance-based designs, emphasizing diagnostic applications.
- Current research prioritizes establishing model performance in structured settings over broader clinical integration.
- This analysis maps the research landscape, offering a reference for understanding ChatGPT's study in oncology.
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