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Multimodal pathological image understanding has garnered widespread interest due to its potential to improve diagnostic accuracy and enable personalized treatment through integrated visual and textual data.
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Wisdom Ikezogwo, Saygin Seyfioglu, Fatemeh Ghezloo, Dylan Geva, Fatwir Sheikh Mohammed, Pavan Kumar Anand, Ranjay Krishna, and Linda Shapiro · 2023
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Eyes wide shut? exploring the visual shortcomings of multimodal llms
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A pathology foundation model for cancer diagnosis and prognosis prediction
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