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%20and%20diagnostic%20captions%20provide%20valuable%20insights%20for%20making%20diagnostic%20decisions.%20However%2C%20aligning%20WSIs%20with%20diagnostic%20captions%20presents%20a%20significant%20challenge.%20This%20difficulty%20arises%20from%20two%20main%20factors:%201)%20Gigapixel%20WSIs%20are%20unsuitable%20for%20direct%20input%20into%20deep%20learning%20models%2C%20and%20the%20redundancy%20and%20correlation%20among%20the%20patches%20demand%20more%20attention%3B%20and%202)%20Authentic%20WSI%20diagnostic%20captions%20are%20extremely%20limited%2C%20making%20it%20difficult%20to%20train%20an%20effective%20model.%20To%20overcome%20these%20obstacles%2C%20we%20present%20PathM3%2C%20a%20multimodal%2C%20multi-task%2C%20multiple%20instance%20learning%20(MIL)%20framework%20for%20WSI%20classification%20and%20captioning.%20PathM3%20adapts%20a%20query-based%20transformer%20to%20effectively%20align%20WSIs%20with%20diagnostic%20captions.%20Given%20that%20histopathology%20visual%20patterns%20are%20redundantly%20distributed%20across%20WSIs%2C%20we%20aggregate%20each%20patch%20feature%20with%20MIL%20method%20that%20considers%20the%20correlations%20among%20instances.%20Furthermore%2C%20our%20PathM3%20overcomes%20data%20scarcity%20in%20WSI-level%20captions%20by%20leveraging%20limited%20WSI%20diagnostic%20caption%20data%20in%20the%20manner%20of%20multi-task%20joint%20learning.%20Extensive%20experiments%20with%20improved%20classification%20accuracy%20and%20caption%20generation%20demonstrate%20the%20effectiveness%20of%20our%20method%20on%20both%20WSI%20classification%20and%20captioning%20task.)
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