Wagholikar, Kavishwar B

Retrieval Augmented Generation Enabled Generative Pre-Trained Transformer 4 (GPT-4) Performance for Clinical Trial Screening

Unlu, O., Shin, J., Mailly, C. J., Oates, M. F., Tucci, M. R., Varugheese, M., Wagholikar, K., Wang, F., Scirica, B. M., Blood, A. J., et al. (2024) · NEJM AI

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 117

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask

Kohane, I. S., Aronow, B. J., Avillach, P., Beaulieu-Jones, B. K., Bellazzi, R., Bradford, R. L., Brat, G. A., Cannataro, M., Cimino, J. J., García-Barrio, N., et al. (2021) · Journal of Medical Internet Research

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 113

Results of a remotely delivered hypertension and lipid program in more than 10?000 patients across a diverse health care network.

Blood, A. J., Cannon, C. P., Gordon, W. J., Mailly, C., MacLean, T., Subramaniam, S., Tucci, M., Crossen, J., Nichols, H., Wagholikar, K. B., et al. (2023) · JAMA Cardiology

Telemedicine and Telehealth ImplementationBlood Pressure and Hypertension Studies

Cited by 108

Comprehensive temporal information detection from clinical text: medical events, time, and TLINK identification

Sohn, S., Wagholikar, K. B., Li, D., Jonnalagadda, S. R., Tao, C., Komandur Elayavilli, R., & Liu, H. (2013) · Journal of the American Medical Informatics Association

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 62

Extraction of ejection fraction from echocardiography notes for constructing a cohort of patients having heart failure with reduced ejection fraction (HFrEF)

Wagholikar, K. B., Fischer, C. M., Goodson, A., Herrick, C. D., Rees, M., Toscano, E., MacRae, C. A., Scirica, B. M., Desai, A. S., & Murphy, S. N. (2018) · Journal of Medical Systems

Artificial Intelligence in HealthcareBiomedical Text Mining and Ontologies

Cited by 27