CT-based hybrid deep learning–radiomics framework for predicting postoperative rebleeding in hypertensive intracerebral hemorrhage

Overall, the integrated nomogram, embedding clinical data, radiomic phenotypes, and deep learning markers, exhibited robust predictive capability in assessing rebleeding risk among patients with HICH. Ongoing research is needed to further refine and validate the model in broader clinical settings.