Baxter, Sally L.

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

Kermany, D. S., Goldbaum, M., Cai, W., Valentim, C. C. S., Liang, H., Baxter, S. L., McKeown, A., Yang, G., Wu, X., Yan, F., et al. (2018) · Cell

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 4,842

The practical implementation of artificial intelligence technologies in medicine

He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019) · Nature Medicine

Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Cited by 2,246

Metrics for assessing physician activity using electronic health record log data

Sinsky, C. A., Rule, A., Cohen, G., Arndt, B. G., Shanafelt, T. D., Sharp, C. D., Baxter, S. L., Tai-Seale, M., Yan, S., Chen, Y., et al. (2020) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 162

AI-Generated Draft Replies Integrated Into Health Records and Physicians’ Electronic Communication

Tai-Seale, M., Baxter, S. L., Vaida, F., Walker, A., Sitapati, A. M., Osborne, C., Diaz, J., Desai, N., Webb, S., Polston, G., et al. (2024) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Cited by 158

Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine

Jin, Q., Chen, F., Zhou, Y., Xu, Z., Cheung, J. M., Chen, R., Summers, R. M., Rousseau, J. F., Ni, P., Landsman, M. J., et al. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 146

Clinical Implementation of Predictive Models Embedded within Electronic Health Record Systems: A Systematic Review

Lee, T. C., Shah, N. U., Haack, A., & Baxter, S. L. (2020) · Informatics

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 133

Semaglutide and Nonarteritic Anterior Ischemic Optic Neuropathy

Cai, C. X., Hribar, M., Baxter, S., Goetz, K., Swaminathan, S. S., Flowers, A., Brown, E. N., Toy, B., Xu, B., Chen, J., et al. (2025) · JAMA Ophthalmology

Diabetes Treatment and ManagementDrug-Induced Ocular Toxicity

Cited by 129

Barriers to Implementing an Artificial Intelligence Model for Unplanned Readmissions

Baxter, S. L., Bass, J. S., & Sitapati, A. M. (2020) · ACI Open

Artificial Intelligence in Healthcare and EducationElectronic Health Records Systems

Cited by 30

Racial Disparities in Barriers to Care for Patients With Diabetic Retinopathy in a Nationwide Cohort

Huang, B. B., Radha Saseendrakumar, B., Delavar, A., & Baxter, S. L. (2023) · Translational Vision Science & Technology

Health disparities and outcomesRetinal Diseases and Treatments

Cited by 29

Advancing Toward a Common Data Model in Ophthalmology

Cai, C. X., Halfpenny, W., Boland, M. V., Lehmann, H. P., Hribar, M., Goetz, K. E., & Baxter, S. L. (2023) · Ophthalmology Science

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 24

Evaluating the neuroprotective impact of senolytic drugs on human vision

El-Nimri, N. W., Moore, S. M., Zangwill, L. M., Proudfoot, J. A., Weinreb, R. N., Skowronska-Krawczyk, D., & Baxter, S. L. (2020) · Scientific Reports

Glaucoma and retinal disordersTelomeres, Telomerase, and Senescence

Cited by 22