Wells et al., 2022
ViewHTML| Publication | Publication Date | Title |
|---|---|---|
| Grant et al. | Use of latent class analysis and k-means clustering to identify complex patient profiles | |
| US12237057B1 (en) | Discovering context-specific complexity and utilization trajectories | |
| Lee et al. | Unlocking the potential of electronic health records for health research | |
| Pivovarov et al. | Learning probabilistic phenotypes from heterogeneous EHR data | |
| Horvath et al. | The DEDUCE Guided Query tool: providing simplified access to clinical data for research and quality improvement | |
| Newton et al. | Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network | |
| Fiore et al. | A point-of-care clinical trial comparing insulin administered using a sliding scale versus a weight-based regimen | |
| Reimer et al. | Veracity in big data: How good is good enough | |
| Daniel et al. | Initializing a hospital-wide data quality program. The AP-HP experience. | |
| Chen et al. | OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records | |
| Espinoza et al. | The need for data standards and implementation policies to integrate CGM data into the electronic health record | |
| US20170061102A1 (en) | Methods and systems for identifying or selecting high value patients | |
| Wong et al. | Role of artificial intelligence in pharmacy practice: a narrative review | |
| Stockwell et al. | Developing a patient safety surveillance system to identify adverse events in the intensive care unit | |
| Lobach et al. | Increasing complexity in rule-based clinical decision support: the symptom assessment and management intervention | |
| Sahoo et al. | Trial prospector: matching patients with cancer research studies using an automated and scalable approach | |
| Jahangir et al. | From Data to Decisions: The AI Revolution in Diabetes Care | |
| Yang et al. | Design and implementation of a depression registry for primary care | |
| Raza et al. | Improving clinical decision making with a two-stage recommender system | |
| Walsh et al. | Device connectivity: the next big wave in diabetes | |
| Singla et al. | Developing clinical decision support system using machine learning methods for type 2 diabetes drug management | |
| Kandaswamy et al. | Pediatric Predictive Artificial Intelligence Implemented in Clinical Practice from 2010-2021: A Systematic Review | |
| Wells et al. | Using electronic health records for the learning health system: creation of a diabetes research registry | |
| US11894117B1 (en) | Discovering context-specific complexity and utilization sequences | |
| Loftus et al. | Longitudinal clinical decision support for assessing decisions over time: State-of-the-art and future directions |