JMIR Medical Informatics
Displaying 1 - 3 of 3
Conderino, S., Anthopolos, R., Albrecht, S. S., Farley, S. M., Divers, J., Titus, A. R., & Thorpe, L. E. (2024). Addressing Information Biases Within Electronic Health Record Data to Improve the Examination of Epidemiologic Associations With Diabetes Prevalence Among Young Adults: Cross-Sectional Study. JMIR Medical Informatics, 12, e58085–e58085. https://doi.org/10.2196/58085
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Columbia Affiliation
Wen, A., Wang, L., He, H., Fu, S., Liu, S., Hanauer, D. A., Harris, D. R., Kavuluru, R., Zhang, R., Natarajan, K., Pavinkurve, N. P., Hajagos, J., Rajupet, S., Lingam, V., Saltz, M., Elowsky, C., Moffitt, R. A., Koraishy, F. M., … Palchuk, M. B. (2024). A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation. JMIR Medical Informatics, 12, e49997. https://doi.org/10.2196/49997
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Columbia Affiliation
Lee, J., & Schnall, R. (2022). Validity and Reliability of the Korean Version of the Health Information Technology Usability Evaluation Scale: Psychometric Evaluation. JMIR Medical Informatics, 10(1), e28621. https://doi.org/10.2196/28621
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Columbia Affiliation