Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive Care IV (MIMIC-IV) Database

database[Title] 2025-05-14

Summary:

CONCLUSIONS: SWEDEHEART-AI, a trained ANN model, demonstrated the best performance, with strong discrimination and clinical utility in predicting 1-year all-cause mortality in patients with AMI from an intensive care cohort. Among the LLMs, Qwen-2 outperformed Llama-3 and showed moderate predictive value. Qwen-2 and SWEDEHEART-AI exhibited comparable classification effectiveness. The future integration of LLMs into clinical decision support systems holds promise for accurate risk stratification...

Link:

https://pubmed.ncbi.nlm.nih.gov/40354652/?utm_source=Other&utm_medium=rss&utm_campaign=pubmed-2&utm_content=12QQbiNmM99eUQGIX1JjHIKcROC1Vzv4sOS-2S_LNI19uG_Yrk&fc=20220129225649&ff=20250514085300&v=2.18.0.post9+e462414

From feeds:

📚BioDBS Bibliography » database[Title]

Tags:

Authors:

Boqun Shi, Liangguo Chen, Shuo Pang, Yue Wang, Shen Wang, Fadong Li, Wenxin Zhao, Pengrong Guo, Leli Zhang, Chu Fan, Yi Zou, Xiaofan Wu

Date tagged:

05/14/2025, 08:55

Date published:

05/12/2025, 06:00