Development of an Artificial Intelligence-Based Automated Recommendation System for Clinical Laboratory Tests: Retrospective Analysis of the National Health Insurance Database.
Md Mohaimenul IslamHsuan-Chia YangTahmina Nasrin PolyYu Chuan Jack LiPublished in: JMIR medical informatics (2020)
The developed artificial intelligence model based on DL exhibited good discriminative capability for predicting laboratory tests using routinely collected EHR data. Utilization of DL approaches can facilitate optimal laboratory test selection for patients, which may in turn improve patient safety. However, future study is recommended to assess the cost-effectiveness for implementing this model in real-world clinical settings.
Keyphrases
- artificial intelligence
- patient safety
- big data
- machine learning
- health insurance
- deep learning
- quality improvement
- end stage renal disease
- electronic health record
- newly diagnosed
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- affordable care act
- high throughput
- sensitive detection
- single cell
- single molecule