Assessment of EMR ML Mining Methods for Measuring Association between Metal Mixture and Mortality for Hypertension
Hypertension patients' mortality associated with heavy metal exposure was predicted by an efficient, robust, and interpretable GA-XGB model with SHAP and LIME. Cadmium, cobalt, lead, tungsten in urine, and mercury in blood are positively correlated with mortality, while barium, molybdenum, antimony, tin, thallium in urine, and lead, selenium, manganese in blood is negatively correlated with mortality.
Authors
- Site Xu (ORCID: https://orcid.org/0000-0003-4317-6041)
- Mu Sun
Institutions
- Ruijin Hospital (CN)
Publication Details
- Journal
- High Blood Pressure & Cardiovascular Prevention
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1007/s40292-024-00666-w
- Citations
- 4
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 1.39