A Machine Learning Approach to Support Urgent Stroke Triage Using Administrative Data and Social Determinants of Health at Hospital Presentation: Retrospective Study.
Min ChenXuan TanRema PadmanPublished in: Journal of medical Internet research (2023)
Using data widely available at the time of patients' hospital presentations, we developed a stroke prediction model with high sensitivity and reasonable specificity. The prediction algorithm uses variables that are routinely collected by providers and payers and might be useful in underresourced hospitals with limited availability of sensitive diagnostic tools or incomplete data-gathering capabilities.
Keyphrases
- machine learning
- healthcare
- big data
- electronic health record
- atrial fibrillation
- end stage renal disease
- emergency department
- ejection fraction
- public health
- chronic kidney disease
- mental health
- artificial intelligence
- prognostic factors
- peritoneal dialysis
- adverse drug
- deep learning
- climate change
- blood brain barrier
- human health