RESEARCHarXiv CS.LG·5/5/2026
Linking spatial biology and clinical histology via Haiku
Haiku is a tri-modal contrastive learning model trained on multiplexed immunofluorescence (mIF), integrating molecular, morphological, and clinical data from over 1,600 patients. It enables three-way cross-modal retrieval, improves downstream classification and clinical prediction tasks, and supports zero-shot biomarker inference, outperforming competing approaches.
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