Evaluation of Decision Compatibility Between a Multidisciplinary Cancer Board and ChatGPT-4O

Overview

This study aims to compare the decisions of a multidisciplinary cancer board at Van research and educational Hospital with those generated by ChatGPT-4O. Patient data, including age, gender, comorbidities, clinical findings, laboratory results, radiology, and pathology reports, will be collected and recorded in patient files. These records will then be converted into a textual format appropriate for input into the ChatGPT-4O model. Statistical analyses will be conducted to assess the level of agreement between the board's decisions and those of ChatGPT-4O, providing insights into their compatibility and potential utility in clinical practice.

This study aims to evaluate the agreement between decisions made by a multidisciplinary cancer board at Van Hospital and those generated by the ChatGPT-4O model. A total of 100 cancer patients presented to the multidisciplinary cancer board will be included in the study. Patient data, including age, gender, comorbidities, clinical findings, laboratory results, radiology, and pathology reports, will be systematically recorded and reformatted into text suitable for the ChatGPT-4O model. The AI model's decisions will then be compared to those made by the cancer board. Statistical analyses will be performed to quantify the level of agreement between the two decision sources. The findings will provide insights into the compatibility between human-led multidisciplinary decisions and AI-driven recommendations, highlighting areas of agreement and disagreement. This study will assess the potential utility of ChatGPT-4O in clinical oncology decision-making and explore whether AI models can support or complement traditional cancer board processes.

Conditions