KM-GPT: An Automated Pipeline for Reconstructing Individual Patient Data from Kaplan-Meier Plots.

ABSTRACT: Reconstructing individual patient data (IPD) from Kaplan-Meier (KM) plots provides valuable insights for evidence synthesis in clinical research. However, existing approaches often rely on manual digitization, which is error-prone and lacks scalability. To address these limitations, we develop KM-GPT, the first fully automated, AI-powered pipeline for reconstructing IPD directly from KM plots with high accuracy, robustness, and reproducibility. KM-GPT integrates advanced image preprocessing, multi-modal reasoning powered by GPT-5, and iterative reconstruction algorithms to generate high-quality IPD without manual input or intervention. Its hybrid reasoning architecture automates the conversion of unstructured information into structured data flows and validates data extraction from complex

SUBMITTER: Zhao Y 

PROVIDER: S-EPMC12458341 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature