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JMIR Medical Informatics|March 5, 2020
Undergraduate Medical Students' Search for Health Information Online: Explanatory Cross-Sectional StudyTeresa Loda, Rebecca Erschens, Florian Junne, et al.
JMIR Medical Informatics|March 5, 2020
Analyzing Medical Research Results Based on Synthetic Data and Their Relation to Real Data Results: Systematic Comparison From Five Observational StudiesAnat Reiner Benaim, Ronit Almog, Yuri Gorelik, et al.
JMIR Medical Informatics|March 5, 2020
Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative StudyLiang Yongping, Ping Zhou, Zhang Juan, et al.
JMIR Medical Informatics|March 5, 2020
Detection of Postictal Generalized Electroencephalogram Suppression: Random Forest ApproachXiaojin Li, Shiqiang Tao, Shirin Jamal-Omidi, et al.
JMIR Medical Informatics|March 19, 2020
Development of a Real-Time Risk Prediction Model for In-Hospital Cardiac Arrest in Critically Ill Patients Using Deep Learning: Retrospective StudyJunetae Kim, Yu Rang Park, Jeong Hoon Lee, et al.
JMIR Medical Informatics|March 13, 2020
A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation StudyEunjoo Jeon, Kyusam Oh, Soonhwan Kwon, et al.
JMIR Medical Informatics|January 24, 2019
Information Technology-Assisted Treatment Planning and Performance Assessment for Severe Thalassemia Care in Low- and Middle-Income Countries: Observational StudyRajat Kumar Agarwal, Amit Sedai, Kumari Ankita, et al.
JMIR Medical Informatics|November 2, 2019
Cohort Selection for Clinical Trials From Longitudinal Patient Records: Text Mining ApproachIrena Spasic, Dominik Krzeminski, Padraig Corcoran, et al.
JMIR Medical Informatics|November 27, 2019
Using a Large Margin Context-Aware Convolutional Neural Network to Automatically Extract Disease-Disease Association from Literature: Comparative Analytic StudyPo-Ting Lai, Wei-Liang Lu, Ting-Rung Kuo, et al.
JMIR Medical Informatics|November 1, 2019
A Bayesian Network Analysis of the Diagnostic Process and Its Accuracy to Determine How Clinicians Estimate Cardiac Function in Critically Ill Patients: Prospective Observational Cohort StudyThomas Kaufmann, José Castela Forte, Bart Hiemstra, et al.
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