Accessibility settings

This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (1497) Clinical Information and Decision Making (3672) Cardiac Risk and Cardiac Risk Calculators (169) Postoperative Cognitive Dysfunction (POCD) (14) Cardiac Surgery (37) Artificial Intelligence in Surgery and Perioperative Medicine (82)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91257, first published .
Two doctors in blue scrubs examining a medical scan

A Multidisciplinary Team–Based Large Language Model Framework for Predicting Postoperative Neurological Complications in Acute Type A Aortic Dissection: Model Development and Validation Study

A Multidisciplinary Team–Based Large Language Model Framework for Predicting Postoperative Neurological Complications in Acute Type A Aortic Dissection: Model Development and Validation Study

Authors of this article:

Jili Li1 Author Orcid Image ;   Julin Zhang2 Author Orcid Image ;   Xingrui Tao3 Author Orcid Image ;   Yaoye Chen3 Author Orcid Image ;   Siqi Xun2 Author Orcid Image ;   Guangshuo Qin4 Author Orcid Image ;   Kaiyue Diao5 Author Orcid Image ;   Chaoyi Qin2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Download .csv
Daily | Monthly | Annually