TaskEvi-Fuse: Task-Adaptive Clinical Evidence Fusion for Multimodal ICU Outcome Prediction

ICU outcome prediction must integrate structured EHR histories, chest radiographs, and radiology reports, although the contribution of each modality may vary by outcome. We present TaskEvi-Fuse, a multimodal clinical prediction framework that combines Gated Residual Modality Alignment (GRMA), which refines representations through gated residual updates and modality-subset experts, with Validation-Controlled Risk Construction (VCRC) for outcome-specific risk-policy selection and calibration. We evaluate the frozen endpoint-specific primary system separately from a controlled common-bank analysis. On a subject-disjoint MIMIC-IV/MIMIC-CXR cohort, using three initializations on one fixed split, the primary system achieves AUROC/AUPRC values of 0.8438/0.4432 for in-hospital mortality, 0.7419/0.7797 for long-stay, and 0.5895/0.3072 for readmission. Among the evaluated protocol-adapted multimodal comparators, it ranks best across the six reported metrics for both long-stay and readmission, and on four of six mortality metrics. Controlled analyses reveal outcome-dependent patterns: different representation variants and risk policies are favored for different endpoints. These findings highlight the value of evaluating multimodal representation refinement and risk construction across clinical outcomes rather than assuming a uniform effect.