The place of advanced machine learning techniques in building pancreatic adenocarcinoma survival and recurrence prognosis models
ML offers a significant advantage in analyzing complex medical data to refine risk stratification and support personalized PDAC treatment. However, current models are limited by their small datasets and retrospective designs. Future research requires prospective validation to translate these ML tools into clinical practice.
Authors
- D Lázár
- Marius-Sorin Murariu (ORCID: https://orcid.org/0000-0002-3045-6282)
- Mihaela Flavia Avram (ORCID: https://orcid.org/0000-0001-8582-521X)
- Michael B. Maris
- Alexandru-Ştefan Cucui-Cozma
Institutions
- Victor Babeș University of Medicine and Pharmacy Timișoara (RO)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-12-17
- DOI
- https://doi.org/10.3389/fonc.2025.1727806
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00