Showing results (831-840 of 2,052) with videos related to

Sort By:
Pageof 206
JMIR Medical Informatics|September 9, 2021
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology PracticeViraj Kulkarni, Manish Gawali, Amit Kharat
JMIR Medical Informatics|August 2, 2022
A Syntactic Information-Based Classification Model for Medical Literature: Algorithm Development and Validation StudyWentai Tang, Jian Wang, Hongfei Lin, et al.
JMIR Medical Informatics|August 2, 2022
Issues With Variability in Electronic Health Record Data About Race and Ethnicity: Descriptive Analysis of the National COVID Cohort Collaborative Data EnclaveLily Cook, Juan Espinoza, Nicole G Weiskopf, et al.
JMIR Medical Informatics|December 9, 2025
Trends and Trajectories in the Rise of Large Language Models in Radiology: Scoping ReviewAdhari Al Zaabi, Rashid Alshibli, Abdullah AlAmri, et al.
JMIR Medical Informatics|November 28, 2025
Unsupervised Coverage Sampling to Enhance Clinical Chart Review Coverage for Computable Phenotype Development: Simulation and Empirical StudyZigui Wang, Jillian H Hurst, Chuan Hong, et al.
JMIR Medical Informatics|December 18, 2025
A Machine Learning Approach to Predicting Mortality Risk in Chemotherapy-Treated Lung Cancer: Machine Learning Model Development and ValidationJianjun Zou, Jinyi Huang, Katie Lu, et al.
JMIR Medical Informatics|December 1, 2025
Identifying Key Variances in Clinical Pathways Associated With Prolonged Hospital Stays Using Machine Learning and ePath Real-World Data: Model Development and Validation StudySaori Tou, Koutarou Matsumoto, Asato Hashinokuchi, et al.
JMIR Medical Informatics|December 2, 2025
Predictive Performance of Radiomics-Based Machine Learning for Colorectal Cancer Recurrence Risk: Systematic Review and Meta-AnalysisYuan Sun, Bo Li, Chuanlan Ju, et al.
JMIR Medical Informatics|November 27, 2025
Risk Prediction of Major Adverse Cardiovascular Events Within One Year After Percutaneous Coronary Intervention in Patients With Acute Coronary Syndrome: Machine Learning-Based Time-to-Event AnalysisHong-Jae Choi, Changhee Lee, Hack-Lyoung Kim, et al.
JMIR Medical Informatics|January 30, 2026
Machine Learning Algorithms to Predict Venous Thromboembolism in Patients With Sepsis in the Intensive Care Unit: Multicenter Retrospective StudyYan Zhang, Xia Ren, Luojie Liu, et al.
Pageof 206