PriOrGen uses prior-anchored modules to debias visual encoding and textual decoding for improved long-tailed multi-organ pathology report generation.
Prototypical informa- tion bottlenecking and disentangling for multimodal cancer survival prediction.arXiv preprint arXiv:2401.01646
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A vision-language model pre-trained via instruction tuning on CT-report pairs improves survival prediction accuracy over baselines, especially when clinical data alone is weak, while also producing text answers to clinical questions.
SlotSPE is a slot-attention framework that decomposes multimodal cancer data into structural prognostic event slots to improve survival prediction and interpretability.
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Prior-Anchored Debiasing for Long-Tailed Multi-Organ Pathology Report Generation
PriOrGen uses prior-anchored modules to debias visual encoding and textual decoding for improved long-tailed multi-organ pathology report generation.
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Medical Image Understanding Improves Survival Prediction via Visual Instruction Tuning
A vision-language model pre-trained via instruction tuning on CT-report pairs improves survival prediction accuracy over baselines, especially when clinical data alone is weak, while also producing text answers to clinical questions.
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Structural Prognostic Event Modeling for Multimodal Cancer Survival Analysis
SlotSPE is a slot-attention framework that decomposes multimodal cancer data into structural prognostic event slots to improve survival prediction and interpretability.