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JMIR Medical Informatics|March 2, 2021
Electronic Health Record Use in Swiss Nursing Homes and Its Association With Implicit Rationing of Nursing Care Documentation: Multicenter Cross-sectional Survey StudyDietmar Ausserhofer, Lauriane Favez, Michael Simon, et al.
JMIR Medical Informatics|July 25, 2019
Projection Word Embedding Model With Hybrid Sampling Training for Classifying ICD-10-CM Codes: Longitudinal Observational StudyChin Lin, Yu-Sheng Lou, Dung-Jang Tsai, et al.
JMIR Medical Informatics|July 13, 2019
Influence of Scribes on Patient-Physician Communication in Primary Care Encounters: Mixed Methods StudyShivang U Danak, Timothy C Guetterman, Melissa A Plegue, et al.
JMIR Medical Informatics|July 13, 2019
Correction: SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value SetsLing Chu, Vaishnavi Kannan, Mujeeb A Basit, et al.
JMIR Medical Informatics|November 2, 2022
Automatic Screening of Pediatric Renal Ultrasound Abnormalities: Deep Learning and Transfer Learning ApproachMing-Chin Tsai, Henry Horng-Shing Lu, Yueh-Chuan Chang, et al.
JMIR Medical Informatics|September 23, 2022
Using Electronic Health Records for the Learning Health System: Creation of a Diabetes Research RegistryBrian J Wells, Stephen M Downs, Brian Ostasiewski
JMIR Medical Informatics|February 4, 2025
Electronic Health Record Use Patterns Among Well-Being Survey Responders and Nonresponders: Longitudinal Observational StudyDaniel Tawfik, Tait D Shanafelt, Mohsen Bayati, et al.
JMIR Medical Informatics|February 6, 2025
An Ontology for Digital Medicine Outcomes: Development of the Digital Medicine Outcomes Value Set (DOVeS)Benjamin Rosner, Matthew Horridge, Guillen Austria, et al.
JMIR Medical Informatics|January 26, 2025
The Impact of Data Control and Delayed Discounting on the Public's Willingness to Share Different Types of Health Care Data: Empirical StudyDongle Wei, Pan Gao, Yunkai Zhai
JMIR Medical Informatics|January 26, 2025
Interpretable Machine Learning Model for Predicting Postpartum Depression: Retrospective StudyRen Zhang, Yi Liu, Zhiwei Zhang, et al.
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