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JMIR Medical Informatics|July 27, 2021
Prediction Model of Anastomotic Leakage Among Esophageal Cancer Patients After Receiving an Esophagectomy: Machine Learning ApproachZiran Zhao, Xi Cheng, Xiao Sun, et al.
JMIR Medical Informatics|September 12, 2018
Defining Empowerment and Supporting Engagement Using Patient Views From the Citizen Health Information Portal: Qualitative StudyTracie Risling, Juan Martinez, Jeremy Young, et al.
JMIR Medical Informatics|July 7, 2017
Issues Associated With the Use of Semantic Web Technology in Knowledge Acquisition for Clinical Decision Support Systems: Systematic Review of the LiteratureSeyedjamal Zolhavarieh, David Parry, Quan Bai
JMIR Medical Informatics|May 9, 2018
Finding Meaning in Medication Reconciliation Using Electronic Health Records: Qualitative Analysis in Safety Net Primary and Specialty CareGeorge Yaccoub Matta, Elaine C Khoong, Courtney R Lyles, et al.
JMIR Medical Informatics|May 17, 2019
Identifying Clinical Terms in Medical Text Using Ontology-Guided Machine LearningAryan Arbabi, David R Adams, Sanja Fidler, et al.
JMIR Medical Informatics|May 9, 2019
Understanding of and Barriers to Electronic Health Record Patient Portal Access in a Culturally Diverse Pediatric PopulationDaniel J Miklin, Sameera S Vangara, Alan M Delamater, et al.
JMIR Medical Informatics|May 9, 2019
Use of Telemedicine to Screen Patients in the Emergency Department: Matched Cohort Study Evaluating Efficiency and Patient Safety of TelemedicineNicholas James Rademacher, Gai Cole, Kevin J Psoter, et al.
JMIR Medical Informatics|May 9, 2019
A Speech-Enabled Fixed-Phrase Translator for Emergency Settings: Crossover StudyHervé Spechbach, Johanna Gerlach, Sanae Mazouri Karker, et al.
JMIR Medical Informatics|November 16, 2017
Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health DatathonPeiyao Li, Chen Xie, Tom Pollard, et al.
JMIR Medical Informatics|December 18, 2019
Efficient Reuse of Natural Language Processing Models for Phenotype-Mention Identification in Free-text Electronic Medical Records: A Phenotype Embedding ApproachHonghan Wu, Karen Hodgson, Sue Dyson, et al.
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