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Self-Supervised AI Reveals a Hidden Landscape of Prognostic Spatial Patterns in Multiplex Immunofluorescence Images

2025-10-16

Abstract excerpt

Modern spatial proteomic methods, such as multiplex immunofluorescence (mIF) imaging, offer a data-rich view of spatial biology in intact tissues. However, interpreting its complexity is a major bottleneck, limiting its potential for biological discovery and clinical translation. Current computational methods often rely on segmentation-based approaches that discard crucial morphological information and are limited...

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Literature Corpus work
c1a30c7c-5c84-5543-915b-0136d27eff68
DOI
10.1101/2025.10.16.682563
Open publication

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Self-Supervised AI Reveals a Hidden Landscape of Prognostic Spatial Patterns in Multiplex Immunofluorescence ImagesDOI 10.1101/2025.10.16.682563
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