GPT-based prediction of short-term survival following decompressive hemicraniectomy in malignant middle cerebral artery infarction.

ABSTRACT:

Introduction

An analysis of the prognostic ability of the large language model (LLM) Generative Pre-trained Transformer (GPT) to predict short-term survival and functional outcomes in patients with malignant middle cerebral artery (MCA) infarction following decompressive hemicraniectomy.

Methods

This retrospective study included 100 patients with malignant MCA infarction who underwent decompressive craniectomy (DC). GPT-4 and GPT-4 Omni were used to predict patient outcomes based on 20 patient-specific factors. Each version of GPT was tested with and without context enrichment (CE). CE versions were provided with the current AHA/ASA 2019 guidelines and meta-analyses of RCTs to inform decision-making. The real-life outcome of the patients, measured by the modified Rankin Scal

SUBMITTER: Lehmann S 

PROVIDER: S-EPMC12329377 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature