Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study. [electronic resource]
Producer: 20190422Description: e1002701 p. digitalISSN:- 1549-1676
- Adolescent
- Adult
- Aged
- Automation
- Comorbidity
- Data Mining -- methods
- Electronic Health Records
- Female
- Health Status
- Humans
- Machine Learning
- Male
- Middle Aged
- Postoperative Complications -- etiology
- Reproducibility of Results
- Retrospective Studies
- Risk Assessment
- Risk Factors
- Surgical Procedures, Operative -- adverse effects
- Young Adult
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Publication Type: Journal Article; Research Support, Non-U.S. Gov't; Validation Study
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