Development and validation of a multimodal machine learning prediction model for heart failure after acute myocardial infarction
Xiaojun Wu, Haoning Cui, Shiyu Wang, Xianghui Zheng, Xinyu Hou, Liyan Ran, Jiaqi Liu, Zhuozhong Wang, Meiqiao Ren, Jing Yao, Huan Ma, Yang Zheng, Jian Wu, Bo Yu · 2026
Read Development and validation of a multimodal machine learning prediction model for heart failure after acute myocardial infarction by Xiaojun Wu, Haoning Cui, Shiyu Wang, Xianghui Zheng, Xinyu Hou, Liyan Ran, Jiaqi Liu, Zhuozhong Wang, Meiqiao Ren, Jing Yao, Huan Ma, Yang Zheng, Jian Wu, Bo Yu (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13534164.txt.
Description
Xiaojun Wu and colleagues build in 2026 a machine learning model to predict heart failure within one year after a heart attack. Current models rest on resting tests and miss how the body performs under effort. Their data held 3,172 patients from three hospitals who had exercise tests from 2018 to 2023.
After screening, 2,221 patients remained and one in ten developed heart failure. The best combined model scored very high in training and strong in outside testing. Adding exercise test data clearly improved sorting of risk, and a web calculator lets clinics flag high-risk patients early.
Catalog record
| CREATOR | Xiaojun Wu, Haoning Cui, Shiyu Wang, Xianghui Zheng, Xinyu Hou, Liyan Ran, Jiaqi Liu, Zhuozhong Wang, Meiqiao Ren, Jing Yao, Huan Ma, Yang Zheng, Jian Wu, Bo Yu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45447 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |