Hanson, C. William

Patient characteristics associated with telemedicine access for primary and specialty ambulatory care during the COVID-19 pandemic.

Eberly, L. A., Kallan, M. J., Julien, H. M., Haynes, N., Khatana, S. A. M., Nathan, A. S., Snider, C., Chokshi, N. P., Eneanya, N. D., Takvorian, S. U., et al. (2020) · JAMA Network Open

Telemedicine and Telehealth ImplementationCOVID-19 and healthcare impacts

Cited by 740

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice*

Giannini, H. M., Ginestra, J. C., Chivers, C., Draugelis, M., Hanish, A., Schweickert, W. D., Fuchs, B. D., Meadows, L., Lynch, M., Donnelly, P. J., et al. (2019) · Critical Care Medicine

Sepsis Diagnosis and TreatmentMachine Learning in Healthcare

Cited by 269

Characteristics, Outcomes, and Trends of Patients With COVID-19–Related Critical Illness at a Learning Health System in the United States

Anesi, G. L., Jablonski, J., Harhay, M. O., Atkins, J. H., Bajaj, J., Baston, C., Brennan, P. J., Candeloro, C. L., Catalano, L. M., Cereda, M. F., et al. (2021) · Annals of Internal Medicine

COVID-19 Clinical Research StudiesRespiratory Support and Mechanisms

Cited by 115

Clinical, Legal, and Ethical Aspects of Artificial Intelligence–Assisted Conversational Agents in Health Care

McGreevey, J. D., Hanson, C. W., & Koppel, R. (2020) · JAMA

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 112