Prediction of Postoperative Mortality After Fontan Procedure: A Clinical Prediction Model Study Using Deep Learning Artificial Intelligence Techniques
A deep learning model that incorporates detailed clinical data can precisely forecast postoperative mortality in patients undergoing Fontan surgeries. This AI-based method, combined with interpretability techniques, provides a valuable tool for personalized risk assessment. It has the potential to improve preoperative counseling, optimize perioperative care, and enhance patient outcomes. However, additional external validation is needed to verify its broader applicability and clinical usefulness.
Authors
- Justyna Stefaniak (ORCID: https://orcid.org/0000-0002-8988-7108)
- Jacek Kołcz (ORCID: https://orcid.org/0000-0003-0704-6389)
- Andrzej A. Kononowicz (ORCID: https://orcid.org/0000-0003-2956-2093)
- Renata Szydlak (ORCID: https://orcid.org/0000-0003-2760-2952)
- Agnieszka Budzyńska
Institutions
- Jagiellonian University (PL)
Publication Details
- Journal
- Journal of Cardiovascular Development and Disease
- Published
- 2025-10-23
- DOI
- https://doi.org/10.3390/jcdd12110420
- Primary Topic
- Congenital Heart Disease Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00