Machine Learning Model for Predicting Mortality Risk in Patients With Complex Chronic Conditions: Retrospective Analysis.
Guillem Hernandez GuillametAriadna Ning Morancho PallarueloLaura Miró MezquitaRamón MirallesMiquel Àngel MasOriol Estrada CuxartFrancesc López SeguíPublished in: Online journal of public health informatics (2023)
This study showcases encouraging outcomes in forecasting mortality among patients with intricate and persistent health conditions. The employed variables are conveniently accessible, and the incorporation of health care resource utilization information of the patient, which has not been employed by current state-of-the-art approaches, displays promising predictive power. The proposed prediction model is designed to efficiently identify cases that need customized care and proactively anticipate the demand for critical resources by health care providers.
Keyphrases
- healthcare
- machine learning
- health information
- public health
- cardiovascular events
- affordable care act
- mental health
- case report
- cardiovascular disease
- artificial intelligence
- adipose tissue
- metabolic syndrome
- big data
- type diabetes
- chronic pain
- weight loss
- drug induced
- insulin resistance
- glycemic control
- health promotion