Utilizing prior-data-fitted networks and in-context learning: a transformer-based tabular foundation model for predicting symptomatic intracranial hemorrhage after successful recanalization
The TabPFN model effectively predicts the risk of sICH in Chinese stroke cohorts, enabling real-time risk stratification for antithrombotic therapy and postoperative blood pressure management.
Authors
- Chengbing Wang (ORCID: https://orcid.org/0000-0002-7437-0974)
- Xiaohua Shi
- Zhongxin Xu
- Zheng Li
- Penglun Sun
- Fenglin Chen
- Jiayue Zhang
- Hui Wang
Institutions
- Union Hospital (HK)
- Capital Medical University (CN)
- Jilin University (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2026-01-12
- DOI
- https://doi.org/10.3389/fneur.2025.1698741
- Primary Topic
- Intracerebral and Subarachnoid Hemorrhage Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00