Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention. [electronic resource]
Producer: 20200820Description: 1304-1311 p. digitalISSN:- 1876-7605
- Aged
- Clinical Decision-Making
- Coronary Artery Disease -- diagnosis
- Decision Support Techniques
- Female
- Heart Failure -- etiology
- Hospital Mortality
- Humans
- Machine Learning
- Male
- Middle Aged
- Minnesota
- Patient Readmission
- Percutaneous Coronary Intervention -- adverse effects
- Predictive Value of Tests
- Registries
- Reproducibility of Results
- Risk Assessment
- Risk Factors
- Time Factors
- Treatment Outcome
No physical items for this record
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Validation Study
There are no comments on this title.
Log in to your account to post a comment.