Landman, Adam

The TRIPOD-LLM reporting guideline for studies using large language models

Gallifant, J., Afshar, M., Ameen, S., Aphinyanaphongs, Y., Chen, S., Cacciamani, G., Demner-Fushman, D., Dligach, D., Daneshjou, R., Fernandes, C., et al. (2025) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 615

Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study

Rao, A., Pang, M., Kim, J., Kamineni, M., Lie, W., Prasad, A. K., Landman, A., Dreyer, K., & Succi, M. D. (2023) · Journal of Medical Internet Research

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 412

Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation

Marwaha, J. S., Landman, A. B., Brat, G. A., Dunn, T., & Gordon, W. J. (2022) · npj Digital Medicine

Electronic Health Records SystemsArtificial Intelligence in Healthcare and Education

Cited by 241

Many Mobile Health Apps Target High-Need, High-Cost Populations, But Gaps Remain

Singh, K., Drouin, K., Newmark, L. P., Lee, J., Faxvaag, A., Rozenblum, R., Pabo, E. A., Landman, A., Klinger, E., & Bates, D. W. (2016) · Health Affairs

Mobile Health and mHealth ApplicationsHealth, Technology, Consumer Behavior

Cited by 201

Assessing the utility of ChatGPT throughout the entire clinical workflow

Rao, A., Pang, M., Kim, J., Kamineni, M., Lie, W., Prasad, A. K., Landman, A., Dreyer, K. J., & Succi, M. D. (2023) · medRxiv

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 134

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

Analysis of errors in dictated clinical documents assisted by speech recognition software and professional transcriptionists

Zhou, L., Blackley, S. V., Kowalski, L., Doan, R., Acker, W. W., Landman, A. B., Kontrient, E., Mack, D., Meteer, M., Bates, D. W., et al. (2018) · JAMA Network Open

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 94

Establishing responsible use of AI guidelines: a comprehensive case study for healthcare institutions

Saenz, A. D., Mass General Brigham AI Governance Committee, McCoy, T., Mantha, A. B., Martin, R., Damiano, R., Adair, D., Heaney, D., Sisodia, R., Park, L., et al. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 62

Clinical trials informed framework for real world clinical implementation and deployment of artificial intelligence applications

You, J. G., Hernandez-Boussard, T., Pfeffer, M. A., Landman, A., & Mishuris, R. G. (2025) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationArtificial Intelligence Applications

Cited by 59