Sjoding, Michael W.

Measuring the Impact of AI in the Diagnosis of Hospitalized Patients: A Randomized Clinical Vignette Survey Study

Jabbour, S., Fouhey, D., Shepard, S., Valley, T. S., Kazerooni, E. A., Banovic, N., Wiens, J., & Sjoding, M. W. (2023) · JAMA

Artificial Intelligence in Healthcare and EducationClinical Reasoning and Diagnostic Skills

Cited by 236

Racial bias and reproducibility in pulse oximetry among medical and surgical inpatients in general care in the Veterans Health Administration 2013-19: multicenter, retrospective cohort study

Valbuena, V. S. M., Seelye, S., Sjoding, M. W., Valley, T. S., Dickson, R. P., Gay, S. E., Claar, D., Prescott, H. C., & Iwashyna, T. J. (2022) · BMJ

Non-Invasive Vital Sign MonitoringRace, Genetics, and Society

Cited by 127

Evaluating a Widely Implemented Proprietary Deterioration Index Model among Hospitalized Patients with COVID-19

Singh, K., Valley, T. S., Tang, S., Li, B. Y., Kamran, F., Sjoding, M. W., Wiens, J., Otles, E., Donnelly, J. P., Wei, M. Y., et al. (2021) · Annals of the American Thoracic Society

COVID-19 Clinical Research StudiesMachine Learning in Healthcare

Cited by 111

Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study

Kamran, F., Tang, S., Otles, E., McEvoy, D. S., Saleh, S. N., Gong, J., Li, B. Y., Dutta, S., Liu, X., Medford, R. J., et al. (2022) · BMJ

Machine Learning in HealthcareCOVID-19 Clinical Research Studies

Cited by 60

Combining chest X-rays and electronic health record (EHR) data using machine learning to diagnose acute respiratory failure

Jabbour, S., Fouhey, D., Kazerooni, E., Wiens, J., & Sjoding, M. W. (2022) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 39

Predicting Intensive Care Transfers and Other Unforeseen Events: Analytic Model Validation Study and Comparison to Existing Methods

Cummings, B. C., Ansari, S., Motyka, J. R., Wang, G., Medlin Jr, R. P., Kronick, S. L., Singh, K., Park, P. K., Napolitano, L. M., Dickson, R. P., et al. (2021) · JMIR Medical Informatics

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 35

Multicenter Prospective Validation of an Updated Proprietary Sepsis Prediction Model

Wong, A., Currey, D., Schwinne, M., Park-Egan, B., Meyer, S., Gutting, A., Cao, J., Khan, S., Dantes, R., Pan, T., et al. (2026) · JAMA Network Open

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 21

External Validation and Comparison of a General Ward Deterioration Index Between Diversely Different Health Systems

Cummings, B. C., Blackmer, J. M., Motyka, J. R., Farzaneh, N., Cao, L., Bisco, E. L., Glassbrook, J. D., Roebuck, M. D., Gillies, C. E., Admon, A. J., et al. (2023) · Critical Care Medicine

Machine Learning in HealthcareSepsis Diagnosis and Treatment

Cited by 19