Artificial Intelligence and Radiomics to Predict Hepatocellular Carcinoma Risk in Cirrhosis Patients
Archived on August 7, 2026. Original response deadline: . Full description on SAM.gov.
Overview
- Response deadline
- 9:00 AM EDT
- Posted
- July 13, 2026
- Notice type
- Presolicitation
- Set-aside
- No Set aside used
- NAICS
- 611310: Colleges, Universities, and Professional Schools
- Agency
- Department of Health and Human ServicesNATIONAL INSTITUTES OF HEALTH
Notice details
- Office
- NATIONAL INSTITUTES OF HEALTH OLAO
- Place of performance
- Bethesda, Maryland, 20892
- PSC
- R799: OTHER MANAGEMENT SUPPORT SERVICES
- Last updated
- Oct 28, 2026
- First published
- Last updated on SAM.gov
Identifiers
- Solicitation number
- 75N98026Q00779
- Notice ID
- b100bda4efeb4d2c85041452b46f76b4
Description
The mission of the National Institute of Diabetes and Digestive and Kidney Diseases is to conduct and support medical research and research training and to disseminate science-based information on diabetes and other endocrine and metabolic diseases; digestive diseases, nutritional disorders, and obesity; and kidney, urologic, and hematologic diseases to improve people’s health and quality of life.
The Liver Diseases Branch is conducting research using radiographic imaging and artificial intelligence to evaluate liver cancer risk in patients with advanced liver disease or cirrhosis. Funding for this effort was awarded through the Bench-to-Bedside and Back Award Program (Award Number 1517448). A portion of the awarded funding will be used to acquire a clinical patient cohort, associated radiographic imaging datasets, and de-identified radiology reports from the University of Pennsylvania.
The research focuses on the use of imaging data and artificial intelligence to improve prediction of liver cancer risk, evaluate liver cancer recurrence following curative therapy, and support translational research related to liver disease and liver cancer. To support these research objectives, the University of Pennsylvania will provide a clinical cohort of patients who underwent liver transplantation for hepatocellular carcinoma, together with associated magnetic resonance imaging studies, radiology reports, and related clinical data necessary for research analysis and model development.
Award Overview
Contacts
Contracting Officer
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- 3Version 3PresolicitationArchivedCurrent
Artificial Intelligence and Radiomics to Predict Hepatocellular Carcinoma Risk in Cirrhosis Patients
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Additional Details
Solicitation Number
75N98026Q00779
Archive Date
Aug 7, 2026
Office Address
BETHESDA, MD, 20892