Klang, Eyal

Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments

Brin, D., Sorin, V., Vaid, A., Soroush, A., Glicksberg, B. S., Charney, A. W., Nadkarni, G., & Klang, E. (2023) · Scientific Reports

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 319

Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19

Vaid, A., Jaladanki, S. K., Xu, J., Teng, S., Kumar, A., Lee, S., Somani, S., Paranjpe, I., Freitas, J. K. D., Wanyan, T., et al. (2020) · JMIR Medical Informatics

Machine Learning in HealthcarePrivacy-Preserving Technologies in Data

Cited by 253

Large Language Models and Empathy: Systematic Review

Sorin, V., Brin, D., Barash, Y., Konen, E., Charney, A., Nadkarni, G., & Klang, E. (2024) · Journal of Medical Internet Research

Artificial Intelligence in Healthcare and EducationEmpathy and Medical Education

Cited by 240

Cross-modality synthesis from CT to PET using FCN and GAN networks for improved automated lesion detection

Ben-Cohen, A., Klang, E., Raskin, S. P., Soffer, S., Ben-Haim, S., Konen, E., Amitai, M. M., & Greenspan, H. (2019) · Engineering Applications of Artificial Intelligence

Medical Imaging Techniques and ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 231

Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support

Omar, M., Sorin, V., Collins, J. D., Reich, D., Freeman, R., Gavin, N., Charney, A., Stump, L., Bragazzi, N. L., Nadkarni, G. N., et al. (2025) · Communications Medicine

Adversarial Robustness in Machine LearningArtificial Intelligence in Healthcare and Education

Cited by 204

Sociodemographic biases in medical decision making by large language models

Omar, M., Soffer, S., Agbareia, R., Bragazzi, N. L., Apakama, D. U., Horowitz, C. R., Charney, A. W., Freeman, R., Kummer, B., Glicksberg, B. S., et al. (2025) · Nature Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 173

Large Language Models Are Poor Medical Coders — Benchmarking of Medical Code Querying

Soroush, A., Glicksberg, B. S., Zimlichman, E., Barash, Y., Freeman, R., Charney, A. W., Nadkarni, G. N., & Klang, E. (2024) · NEJM AI

Medical Coding and Health InformationArtificial Intelligence in Healthcare and Education

Cited by 137

Large language models for generating medical examinations: systematic review

Artsi, Y., Sorin, V., Konen, E., Glicksberg, B. S., Nadkarni, G., & Klang, E. (2024) · BMC Medical Education

Artificial Intelligence in Healthcare and EducationInnovations in Medical Education

Cited by 128

Artificial intelligence-aided colonoscopy does not increase adenoma detection rate in routine clinical practice

Levy, I., Bruckmayer, L., Klang, E., Ben-Horin, S., & Kopylov, U. (2022) · American Journal of Gastroenterology

Colorectal Cancer Screening and DetectionAI in cancer detection

Cited by 114

Evaluating the use of large language model in identifying top research questions in gastroenterology

Lahat, A., Shachar, E., Avidan, B., Shatz, Z., Glicksberg, B. S., & Klang, E. (2023) · Scientific Reports

Artificial Intelligence in Healthcare and EducationArtificial Intelligence Applications

Cited by 111

Evaluating and addressing demographic disparities in medical large language models: a systematic review

Omar, M., Sorin, V., Agbareia, R., Apakama, D. U., Soroush, A., Sakhuja, A., Freeman, R., Horowitz, C. R., Richardson, L. D., Nadkarni, G. N., et al. (2025) · International Journal for Equity in Health

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 110

Trend in radiologist workload compared to number of admissions in the emergency department

Dan Lantsman, C., Barash, Y., Klang, E., Guranda, L., Konen, E., & Tau, N. (2022) · European Journal of Radiology

Radiology practices and educationEmergency and Acute Care Studies

Cited by 85

Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room

Glicksberg, B. S., Timsina, P., Patel, D., Sawant, A., Vaid, A., Raut, G., Charney, A. W., Apakama, D., Carr, B. G., Freeman, R., et al. (2024) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 82

Utilizing natural language processing and large language models in the diagnosis and prediction of infectious diseases: A systematic review

Omar, M., Brin, D., Glicksberg, B., & Klang, E. (2024) · American Journal of Infection Control

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 59

Benchmarking the confidence of large language models in answering clinical questions: Cross-sectional evaluation study

Omar, M., Agbareia, R., Glicksberg, B. S., Nadkarni, G. N., & Klang, E. (2025) · JMIR Medical Informatics

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 53

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

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

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

Retrieval-Augmented Generation: Advancing personalized care and research in oncology

Zarfati, M., Soffer, S., Nadkarni, G. N., & Klang, E. (2025) · European Journal of Cancer

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 20

Deep learning in voice analysis for diagnosing vocal cord pathologies: a systematic review

Tessler, I., Primov-Fever, A., Soffer, S., Anteby, R., Gecel, N. A., Livneh, N., Alon, E. E., Zimlichman, E., & Klang, E. (2024) · European Archives of Oto-Rhino-Laryngology

Voice and Speech DisordersArtificial Intelligence in Healthcare

Cited by 18

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