AI RESEARCH
A Multimodal Deep Learning Framework for Edema Classification Using HCT and Clinical Data
arXiv CS.AI
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ArXi:2603.26726v1 Announce Type: cross We propose AttentionMixer, a unified deep learning framework for multimodal detection of brain edema that combines structural head CT (HCT) with routine clinical metadata. While HCT provides rich spatial information, clinical variables such as age, laboratory values, and scan timing capture complementary context that might be ignored or naively concatenated. AttentionMixer is designed to fuse these heterogeneous sources in a principled and efficient manner.