Glicksberg, Benjamin S.

OCTAD: an open workspace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features

Zeng, B., Glicksberg, B. S., Newbury, P., Chekalin, E., Xing, J., Liu, K., Wen, A., Chow, C., & Chen, B. (2021) · Nature Protocols

Computational Drug Discovery MethodsGene expression and cancer classification

Cited by 48

The association between obesity and peak antibody titer response in COVID‐19 infection

Soffer, S., Glicksberg, B. S., Zimlichman, E., Efros, O., Levin, M. A., Freeman, R., Reich, D. L., & Klang, E. (2021) · Obesity

COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 Research

Cited by 48

PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model

Glicksberg, B. S., Oskotsky, B., Thangaraj, P. M., Giangreco, N., Badgeley, M. A., Johnson, K. W., Datta, D., Rudrapatna, V. A., Rappoport, N., Shervey, M. M., et al. (2019) · Bioinformatics

Electronic Health Records SystemsMachine Learning in Healthcare

Cited by 45

Deep phenotyping of Alzheimer’s disease leveraging electronic medical records identifies sex-specific clinical associations

Tang, A. S., Oskotsky, T., Havaldar, S., Mantyh, W. G., Bicak, M., Solsberg, C. W., Woldemariam, S., Zeng, B., Hu, Z., Oskotsky, B., et al. (2022) · Nature Communications

Dementia and Cognitive Impairment ResearchMachine Learning in Healthcare

Cited by 45

Generating credible referenced medical research: A comparative study of openAI's GPT-4 and Google's gemini

Omar, M., Nassar, S., Hijazi, K., Glicksberg, B. S., Nadkarni, G. N., & Klang, E. (2025) · Computers in Biology and Medicine

Artificial Intelligence in Healthcare and EducationAcademic Writing and Publishing

Cited by 43

Unmasking fracture risk in type 2 diabetes: the association of longitudinal glycemic hemoglobin level and medications

Wang, B., Wang, Z., Poundarik, A. A., Zaki, M. J., Bockman, R. S., Glicksberg, B. S., Nadkarni, G. N., & Vashishth, D. (2022) · The Journal of Clinical Endocrinology & Metabolism

Bone health and osteoporosis researchDiabetes Treatment and Management

Cited by 37

ChatGPT: A Conceptual Review of Applications and Utility in the Field of Medicine

Rao, S. J., Isath, A., Krishnan, P., Tangsrivimol, J. A., Virk, H. U. H., Wang, Z., Glicksberg, B. S., & Krittanawong, C. (2024) · Journal of Medical Systems

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 35

Multi-center retrospective cohort study applying deep learning to electrocardiograms to identify left heart valvular dysfunction

Vaid, A., Argulian, E., Lerakis, S., Beaulieu-Jones, B. K., Krittanawong, C., Klang, E., Lampert, J., Reddy, V. Y., Narula, J., Nadkarni, G. N., et al. (2023) · Communications Medicine

ECG Monitoring and AnalysisMachine Learning in Healthcare

Cited by 30

Applications of artificial intelligence in vasculitides: a systematic review

Omar, M., Agbareia, R., Naffaa, M. E., Watad, A., Glicksberg, B. S., Nadkarni, G. N., & Klang, E. (2025) · ACR Open Rheumatology

Kawasaki Disease and Coronary ComplicationsVasculitis and related conditions

Cited by 11

Benchmarking the Confidence of Large Language Models in Clinical Questions

Omar, M., Agbareia, R., Glicksberg, B. S., Nadkarni, G. N., & Klang, E. (2024) · medRxiv

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 10

“Large language models in radiology reporting—a systematic review of performance, limitations, and clinical implications”

Artsi, Y., Klang, E., Collins, J. D., Glicksberg, B. S., Korfiatis, P., Nadkarni, G. N., & Sorin, V. (2025) · medRxiv

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 7

Assessing retrieval-augmented large language models for medical coding

Klang, E., Tessler, I., Apakama, D. U., Abbott, E., Glicksberg, B. S., Arnold, M., Moses, A., Sakhuja, A., Soroush, A., Charney, A. W., et al. (2025) · NEJM AI

Medical Coding and Health InformationMachine Learning in Healthcare

Cited by 6

Cloud Platforms for Developing Generative AI Solutions: A Scoping Review of Tools and Services

Patel, D., Raut, G., Cheetirala, S. N., Nadkarni, G. N., Freeman, R., Glicksberg, B. S., Klang, E., & Timsina, P. (2024) · arXiv

Cloud Computing and Resource ManagementArtificial Intelligence Applications

Cited by 5