Benzo, R. M., Gogineni, A., Tetrick, M. K., Singh, R., Washington, P., Fernandez, S., … & Addison, D. (2025). mHealth technologies in research studying cardiovascular health in cancer: A systematic review. PLOS Digital Health, 4(9), e0001027.
Optimising large language models for clinical information extraction: a benchmarking study in the context of ulcerative colitis research
Yim, R.P., Silverman, A.L., Wang, S., Rudrapatna, V.A. Optimising large language models for clinical information extraction: a benchmarking study in the context of ulcerative colitis research. BMJ Digital Health & AI. 2025;1:e000014.
Reimagining clinical AI: from clickstreams to clinical insights with EHR use metadata
Yan, C., Zhang, X., Kannampallil, T.G. Adler-Milstein, J., & Chen, Y. Reimagining clinical AI: from clickstreams to clinical insights with EHR use metadata. npj Health Syst. 2, 33 (2025). https://doi.org/10.1038/s44401-025-00040-5.
Automated Radiation Response Assessment with Deep Learning and Radiomics in Pediatric Diffuse Midline Glioma
Mojahed-Yazdi, R., Zielke, J., Zapaishchykova, A., Tak, D., Mussa, F. R., Ye, Z., … Rauschecker, A.,… & Kann, B. H. (2025). Automated Radiation Response Assessment with Deep Learning and Radiomics in Pediatric Diffuse Midline Glioma. International Journal of Radiation Oncology* Biology* Physics, 123(1), e194.
Multi-Institutional Validation of the SHIELD-RT Machine Learning Model to Prevent Acute Care Events during Radiotherapy
Elia, M. V., Benson, R., Bhargava, N., Levey, J., Eclov, N., Friesner, I., … Feng, J., … & Hong, J. C. (2025). Multi-Institutional Validation of the SHIELD-RT Machine Learning Model to Prevent Acute Care Events during Radiotherapy. International Journal of Radiation Oncology* Biology* Physics, 123(1), S74-S75.
PRIME 2.0: An Update to The Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation Checklist.
Kagiyama, N., Tokodi, M., Hathaway, Q. A., Arnaout, R., Davies, R., Dey, D., … & Sengupta, P. P. (2025). PRIME 2.0: An Update to The Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation Checklist. JACC: Cardiovascular Imaging.
Laslo, D., Nguyen, B., Suhami, D., Mueller, T., Lipina, J., Mir, N., … Rauschecker, A., … & Brüningk, S. (2025). IMG-04. Anatomical tumor growth predictions in pediatric diffuse midline glioma using generative AI. Neuro-Oncology Pediatrics, 1(Supplement_1), wuaf001-166.
Laslo, D., Nguyen, B., Suhami, D., Mueller, T., Lipina, J., Mir, N., … Rauschecker, A., … & Brüningk, S. (2025). IMG-04. Anatomical tumor growth predictions in pediatric diffuse midline glioma using generative AI. Neuro-Oncology Pediatrics, 1(Supplement_1), wuaf001-166.
Chen, I. Y., & Alsentzer, E. (2025). Redefining Bias Audits for Generative AI in Health Care. NEJM AI, AIp2500015.
Chen, I. Y., & Alsentzer, E. (2025). Redefining Bias Audits for Generative AI in Health Care. NEJM AI, AIp2500015.
Mehta, S., Brown III, W., Sarkar, U., Tran, N., Hswen, Y., & Pantell, M. S. (2025). Examining housing insecurity and transportation barriers in pediatric hospital readmissions: insights from structured and unstructured data. Journal of the American Medical Informatics Association, ocaf135.
Mehta, S., Brown III, W., Sarkar, U., Tran, N., Hswen, Y., & Pantell, M. S. (2025). Examining housing insecurity and transportation barriers in pediatric hospital readmissions: insights from structured and unstructured data. Journal of the American Medical Informatics Association, ocaf135.
Kim, S., Kannampallil, T., Wick, B. D., Holmgren, A. J., Thombley, R., & Lou, S. S. (2025). Exploring Task Patterns in EHR Workflows Using Action Sequence Embedding and Graph-Based Analysis. Studies in health technology and informatics, 329, 1281–1285.
Kim, S., Kannampallil, T., Wick, B. D., Holmgren, A. J., Thombley, R., & Lou, S. S. (2025). Exploring Task Patterns in EHR Workflows Using Action Sequence Embedding and Graph-Based Analysis. Studies in health technology and informatics, 329, 1281–1285.