Hersh Sagreiya, MD
Radiology
Accepting new patients
Sees patients age 18 and up
Headshot of Hersh Sagreiya, MD
Penn Medicine Provider

About me

  • Assistant Professor of Radiology at the Hospital of the University of Pennsylvania

Physician-scientist, with clinical work in Abdominal Imaging and research in Informatics and Machine Learning.

Education and training

  • Medical School: Stanford University School of Medicine
  • Residency: Abington Memorial Hospital
  • Residency: University of Pittsburgh School of Medicine
  • Fellowship: Stanford University

Insurance accepted

My Locations

Penn Medicine hospital privileges

  • Hospital of the University of Pennsylvania: Has privileges to treat patients in the hospital.
  • Pennsylvania Hospital: Has privileges to treat patients in the hospital.
  • Penn Presbyterian Medical Center: Has privileges to treat patients in the hospital.
  • Penn Medicine Rittenhouse Long-Term Acute Care Hospital
  • Chester County Hospital: Has privileges to treat patients in the hospital.
Dr. Sagreiya is a Penn Medicine physician.

Qualifications and experience

Treatments and Conditions

My research

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


Ghonim, M., Ghonim, M., Castro-Aragon, I., Akhbardeh, A., Sehgal, C., Sagreiya, H. Inter-Rater Reliability of Transverse and Sagittal Pediatric Lung Ultrasonography for Detecting Pulmonary Findings in Children with Pneumonia. , 2026 American Institute for Ultrasound in Medicine Annual Convention: 2026


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


Yeung, J., Sehgal, C., Sagreiya, H. Lung Ultrasound: Utility and Role in Differentiating Alveolar-Interstitial Syndromes. , American Roentgen Ray Society 2026: 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: 2026,1-10


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


Byun, S., Sagreiya, H. Hemothorax Quantification with AI: Background, Current Research, and Future Frontiers. , Chest Imaging - Science and Practice: 2026


Zhuang, R., Borthakur, A., Kahn, C.E., Duda, J., Rader, D., Gee, J.C., Witschey, W.R., Sagreiya, H. Application of Deep Learning-Based CT Quantification of Muscle, Visceral Fat, and Intramuscular Fat to Identify Laboratory and Clinical Risk Factors for Sarcopenia. , Radiological Society of North America: 2025


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