Automated-detection of risky alcohol use prior to surgery using natural language processing.
V G Vinod VydiswaranAsher StrayhornKatherine WeberHaley StevensJessica MellingerG Scott WinderAnne C FernandezPublished in: Alcohol, clinical & experimental research (2024)
NLP, an artificial intelligence-based approach, efficiently and accurately identifies alcohol-related risk in patients' EHRs. This approach could supplement other alcohol screening tools to identify patients in need of intervention, treatment, and/or postoperative withdrawal prophylaxis. Alcohol-related ICD diagnosis had limited utility relative to NLP, which extracts richer information within clinical notes to classify patients.
Keyphrases
- end stage renal disease
- artificial intelligence
- ejection fraction
- newly diagnosed
- chronic kidney disease
- machine learning
- prognostic factors
- healthcare
- deep learning
- patients undergoing
- gene expression
- autism spectrum disorder
- patient reported outcomes
- dna methylation
- social media
- acute coronary syndrome
- alcohol consumption
- high throughput
- percutaneous coronary intervention
- atrial fibrillation
- drug induced
- single cell
- coronary artery bypass