Bakr, A., Garcia-Agundez, A., Atkison, T., Rudrapatna, V. A., & Gupta, T. (2026). MEDAL: Sequential adapter learning for privacy-preserving multicenter clinical language models. Journal of Biomedical Informatics, Article 105101. https://doi.org/10.1016/j.jbi.2026.105101
Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease
Kamineni, M., Raghu, V., Hua, Z., Tian, H., Truong, B., Alaa, A., Schuermans, A., Friedman, S., Reeder, C., Bhattacharya, R., Libby, P., Ellinor, P. T., Maddah, M., Philippakis, A., Hornsby, W., Yu, Z., & Natarajan, P. (2026). Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease. Science Translational Medicine, 18(866), eaeh2517. https://doi.org/10.1126/scitranslmed.aeh2517
Investigating social bias changes in quantized large language models
Hua, S. B. Z., Lotfi, S., & Chen, I. Y. (2026). Investigating social bias changes in quantized large language models. In Proceedings of the Third Conference on Language Modeling. https://openreview.net/forum?id=sr6xTPBZ5b
Adaptive auditing of AI systems with anytime-valid guarantees
Zhou, S., Vossler, P., Sivaraman, V., Mai, Y., & Feng, J. (2026). Adaptive auditing of AI systems with anytime-valid guarantees. Advances in Neural Information Processing Systems. https://doi.org/10.48550/arXiv.2605.07002
Artificial intelligence-based speech error detection to differentiate primary progressive aphasia variants
Vonk, J. M. J., Lian, J., Kurteff, G. L., Cho, C. J., Antonicelli, G., Ezzes, Z., Wauters, L. D., Keegan-Rodewald, W., Rodriguez, D. A., Dronkers, N., Henry, M. L., Miller, Z. A., Mandelli, M. L., Anumanchipalli, G. K., & Gorno-Tempini, M. L. (2026). Artificial intelligence-based speech error detection to differentiate primary progressive aphasia variants. Brain Communications, 8(5), fcag353. https://doi.org/10.1093/braincomms/fcag353
Opportunistic Chest CT Paraspinal Muscle Biomarkers to Predict Longitudinal Thoracic Vertebral Bone Mineral Density Loss: Results from MESA
Hathaway, Q. A., Ghotbi, E., Pan, T., Momtazmanesh, S., Klein, J. G., Allison, M., Mortani Barbosa, E. J., Jr., Barr, R. G., Bluemke, D. A., Lima, J. A. C., Post, W., Tison, G. H., Ambale-Venkatesh, B., Budoff, M., & Demehri, S. (2026). Opportunistic chest CT paraspinal muscle biomarkers to predict longitudinal thoracic vertebral bone mineral density loss: Results from MESA. Radiology, 320(3). https://doi.org/10.1148/radiol.260238
Why exercise does not work equally well for everyone: Life-course conditions and the limits of precision medicine.
Horwitz, R. I., Hayes Conroy, A., Cullen, M. R., Matory, A., & Sim, I. (2026). Why exercise does not work equally well for everyone: Life-course conditions and the limits of precision medicine. The American Journal of Medicine. Advance online publication. https://doi.org/10.1016/j.amjmed.2026.08.023
Transporting a pediatric surgical site infection prediction model to the electronic health record: external validation, harmonization, and recalibration
Chan, C. T., Pletcher, M. J., Balakrishnan, K., Hswen, Y., Scheffler, A. (2026). Transporting a pediatric surgical site infection prediction model to the electronic health record: External validation, harmonization, and recalibration. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocag162
Narang, K., Addo, N., Williams, C. Y. K., Firnberg, M., Feng, J., & Kornblith, A. (2026). Assessing acuity in pediatric emergency department triage: Performance of a large language model. npj Health Systems, 3, Article 68. https://doi.org/10.1038/s44401-026-00128-6
Narang, K., Addo, N., Williams, C. Y. K., Firnberg, M., Feng, J., & Kornblith, A. (2026). Assessing acuity in pediatric emergency department triage: Performance of a large language model. npj Health Systems, 3, Article 68. https://doi.org/10.1038/s44401-026-00128-6
Kishore, S. P., Narang, P., & Auerbach, A. (2026). Sorting results of unknown significance—A framework for clinicians navigating wearable data in the AI era. JAMA, 336(9), 733–735. https://doi.org/10.1001/jama.2026.13895
Kishore, S. P., Narang, P., & Auerbach, A. (2026). Sorting results of unknown significance—A framework for clinicians navigating wearable data in the AI era. JAMA, 336(9), 733–735. https://doi.org/10.1001/jama.2026.13895

