Explainable Machine Learning and Online Calculators to Predict Heart Failure Mortality in Intensive Care Units
The study developed an LDA and a nomogram model for predicting mortality in HF patients in the ICU. The SHAP approach was employed to elucidate the LDA model, enhancing its utility for clinicians. These models were made accessible online for clinical application.
Authors
- An‐Tian Chen (ORCID: https://orcid.org/0000-0002-2829-7921)
- Jian Zhang (ORCID: https://orcid.org/0000-0002-8778-4797)
- Yuhui Zhang (ORCID: https://orcid.org/0000-0002-4373-1845)
Institutions
- Austin College (US)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- National Health and Family Planning Commission (CN)
- Fu Wai Hospital (CN)
- The University of Texas at Austin (US)
Publication Details
- Journal
- ESC Heart Failure
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1002/ehf2.15062
- Citations
- 7
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 2.43
Funders
- Natural Science Foundation of Beijing Municipality
- Chinese Academy of Medical Sciences
- Fuwai Hospital, Chinese Academy of Medical Sciences
- Chinese Academy of Medical Sciences Initiative for Innovative Medicine