Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation.
Zhi-Geng JinHui ZhangMei-Hui TaiYing YangYuan YaoYu-Tao GuoPublished in: Journal of medical Internet research (2023)
The NLP algorithm in our DeVTEcare identified VTE well across different clinical settings, especially in patients in surgery units, departments with low-risk VTE, and patients aged ≤65 years. This algorithm can help to inform accurate in-hospital VTE rates and enhance risk-classified VTE integrated care in future research.
Keyphrases
- venous thromboembolism
- end stage renal disease
- direct oral anticoagulants
- clinical decision support
- newly diagnosed
- chronic kidney disease
- ejection fraction
- machine learning
- healthcare
- deep learning
- minimally invasive
- prognostic factors
- autism spectrum disorder
- high resolution
- coronary artery disease
- electronic health record
- percutaneous coronary intervention
- adverse drug
- chronic pain