Target-based fusion using social determinants of health to enhance suicide prediction with electronic health records.
Shane J SaccoKun ChenFei WangRobert H AseltinePublished in: PloS one (2023)
This proof-of-concept study showed that incorporating social determinants measures from an external survey database could improve prediction of youth suicide risk from clinical data using a data fusion framework. While social determinant data directly from patients might be ideal, estimating these characteristics via data fusion avoids the task of data collection, which is generally time-consuming, expensive, and suffers from non-compliance.
Keyphrases
- electronic health record
- big data
- healthcare
- mental health
- clinical decision support
- end stage renal disease
- cross sectional
- adverse drug
- physical activity
- peritoneal dialysis
- risk assessment
- young adults
- machine learning
- prognostic factors
- chronic kidney disease
- climate change
- health information
- artificial intelligence
- human health