Published on in Vol 25 (2023)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/47664, first published
.
![Development and Validation of Machine Learning–Based Models to Predict In-Hospital Mortality in Life-Threatening Ventricular Arrhythmias: Retrospective Cohort Study Development and Validation of Machine Learning–Based Models to Predict In-Hospital Mortality in Life-Threatening Ventricular Arrhythmias: Retrospective Cohort Study](https://asset.jmir.pub/assets/d724378eb79b1b9fbf68fe37962d090e.png 480w,https://asset.jmir.pub/assets/d724378eb79b1b9fbf68fe37962d090e.png 960w,https://asset.jmir.pub/assets/d724378eb79b1b9fbf68fe37962d090e.png 1920w,https://asset.jmir.pub/assets/d724378eb79b1b9fbf68fe37962d090e.png 2500w)
Journals
- 夏来百提姑 ·. Research Progress of In-Hospital Cardiac Ar-rest Early Warning Model Based on Machine Learning. Advances in Clinical Medicine 2024;14(01):871 View
- Hu Z, Wang M, Zheng S, Xu X, Zhang Z, Ge Q, Li J, Yao Y. Clinical Decision Support Requirements for Ventricular Tachycardia Diagnosis Within the Frameworks of Knowledge and Practice: Survey Study. JMIR Human Factors 2024;11:e55802 View