Artificial Intelligence can Facilitate Application of Risk Stratification Algorithms to Bladder Cancer Patient Case Scenarios.

ABSTRACT:

Background

Chat Generative Pre-Trained Transformer (ChatGPT) has previously been shown to accurately predict colon cancer screening intervals when provided with clinical data and context in the form of guidelines. The National Comprehensive Cancer Network^® (NCCN^®) guideline on non-muscle invasive bladder cancer (NMIBC) includes criteria for risk stratification into low-, intermediate-, and high-risk groups based on patient and disease characteristics. The aim of this study is to evaluate the ability of ChatGPT to apply the NCCN Guidelines to risk stratify theoretical patient scenarios related to NMIBC.

Methods

Thirty-six hypothetical patient scenarios related to NMIBC were created and submitted to GPT-3.5 and GPT-4 at two separate time points. First, bo

SUBMITTER: Yudovich MS 

PROVIDER: S-EPMC11571244 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature