Dreyer, Keith J.

Federated learning for predicting clinical outcomes in patients with COVID-19

Dayan, I., Roth, H. R., Zhong, A., Harouni, A., Gentili, A., Abidin, A. Z., Liu, A., Costa, A. B., Wood, B. J., Tsai, C.-S., et al. (2021) · Nature Medicine

Machine Learning in HealthcareCOVID-19 diagnosis using AI

Cited by 842

Current Applications and Future Impact of Machine Learning in Radiology

Choy, G., Khalilzadeh, O., Michalski, M., Do, S., Samir, A. E., Pianykh, O. S., Geis, J. R., Pandharipande, P. V., Brink, J. A., & Dreyer, K. J. (2018) · Radiology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 800

Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success

Thrall, J. H., Li, X., Li, Q., Cruz, C., Do, S., Dreyer, K., & Brink, J. (2018) · Journal of the American College of Radiology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 710

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

When Machines Think: Radiology’s Next Frontier

Dreyer, K. J., & Geis, J. R. (2017) · Radiology

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 183

Association of Artificial Intelligence–Aided Chest Radiograph Interpretation With Reader Performance and Efficiency

Ahn, J. S., Ebrahimian, S., McDermott, S., Lee, S., Naccarato, L., Di Capua, J. F., Wu, M. Y., Zhang, E. W., Muse, V., Miller, B., et al. (2022) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationRadiology practices and education

Cited by 138

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

FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies

Ebrahimian, S., Kalra, M. K., Agarwal, S., Bizzo, B. C., Elkholy, M., Wald, C., Allen, B., & Dreyer, K. J. (2022) · Academic Radiology

Artificial Intelligence in Healthcare and EducationAI in cancer detection

Cited by 120

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

Errare Humanum Est: Frequency of Laterality Errors in Radiology Reports

Sangwaiya, M. J., Saini, S., Blake, M. A., Dreyer, K. J., & Kalra, M. K. (2009) · American Journal of Roentgenology

Radiology practices and educationPatient Safety and Medication Errors

Cited by 37

Artificial Intelligence in Health Care: Brave New World or Golden Opportunity?

Dreyer, K., & Allen, B. (2018) · Journal of the American College of Radiology

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 28

Assessing Laterality Errors in Radiology: Comparing Generative Artificial Intelligence and Natural Language Processing

Kathait, A. S., Garza-Frias, E., Sikka, T., Schultz, T. J., Bizzo, B., Kalra, M. K., & Dreyer, K. J. (2024) · Journal of the American College of Radiology

Artificial Intelligence in Healthcare and EducationRadiology practices and education

Cited by 11