Barinov, L. Scott, J., Sagreiya, H. Towards the operationalization of artificial intelligence in thyroid ultrasound imaging. , 2026 American Institute for Ultrasound in Medicine Annual Convention: 2026

Tran, R.H., Raghupathy, P., Hazim, M., Thompson, E., Swago, S., Bhattaru, A., MacLean, M., Duda, J.T., Gee, J., Kahn, C., Rader, D.J., Borthakur, A., Witschey, W.R., Sagreiya, H. Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on CT scans. , Diabetes, Obesity and Metabolism, 28(5): 2026,3742-3751

Wang, E., Sagreiya, H., Escamilla-Ocanas, C., Hirzallah, M., Akhbardeh, A., Morales-Cardona, N. Machine Learning for Automated Multi-Class Segmentation and Measurement of Optic Nerve Structures. , 2026 American Institute for Ultrasound in Medicine Annual Convention: 2026

Sagreiya, H. Reply to “Minimizing Medical Malpractice Risk for Radiologists Using Artificial Intelligence.” , American Journal of Roentgenology, 226(4): 2026,e2534161

Sagreiya, H. Can Artificial Intelligence Doom a Radiologist in Malpractice Cases, and Can This Risk be Mitigated? , American Journal of Roentgenology, 226(4): 2026,e2533720

Yeung, J., Sehgal, C., Sagreiya, H. Lung Ultrasound: Utility and Role in Differentiating Alveolar-Interstitial Syndromes. , American Roentgen Ray Society 2026: 2026

Till, J.E., Gal-Rosenberg, O., Gilberto, S.G., Seewald, N.J., Ballinger, D.G., Samberg, H.E., Yin, M.R., Wang, Q., Cannas, S., Kim, K.N., Tien, K., Sawi, M., Madineedi, V., Furniss, S., Gocheva, V., Nowak, J., Brais, L.K., Yuan, C., Rosenthal, M.H., Roses, R., DeMatteo, R., Lee, M.K., Vollmer, C., Sagreiya, H., O’Hara, M.H., Shemer, R., Wolpin, B., Dor, Y., Carpenter, E.L. Plasma cell-free DNA markers predict occult metastases in patients with resectable pancreatic ductal adenocarcinoma. , Clinical and Translational Medicine, 16(1): 2026,e70573

Meng, S., Sagreiya, H., Orangi-Fard, N. Prediction of Chronic Obstructive Pulmonary Disease Using Machine Learning, Clinical Summary Notes, and Vital Signs: A Single-Center Retrospective Cohort Study in the United States. , Advances in Respiratory Medicine, 94(1): 2026,5

Sundaram, K.M., Sagreiya, H., Rosen, M.A. Editorial for “Preoperative Assessment of Extraprostatic Extension in Prostate Cancer Using an Interpretable Tabular Prior-Data Fitted Network-Based Radiomics Model From MRI.” , Journal of Magnetic Resonance Imaging, 63(1): 2026,113-114