Advancing Pancreatic Cancer Prediction with a Next Visit Token Prediction Head on Top of Med-BERT
Reformatting disease prediction tasks to align with the pretraining of foundation models enhances prediction accuracy, leading to earlier detection and timely intervention. This approach improves treatment effectiveness, survival rates, and overall patient outcomes for PaCa and potentially other cancers.
Authors
- Degui Zhi (ORCID: https://orcid.org/0000-0001-7754-1890)
- Laila Rasmy (ORCID: https://orcid.org/0000-0002-2644-4908)
- Cui Tao (ORCID: https://orcid.org/0000-0002-4267-1924)
- Jianping He (ORCID: https://orcid.org/0000-0002-2395-3096)
Institutions
- Mayo Clinic in Florida (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Cancers
- Published
- 2025-02-04
- DOI
- https://doi.org/10.3390/cancers17030516
- Citations
- 3
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 7.44
Funders
- American Heart Association