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Department of Computer Science, Harvard University, USA
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MixTIME reveals that integrating diverse image modalities can significantly enhance the precision of immune biomarker predictions in oncology, outperforming traditional single-modality approaches.
Imagine a medical "Google" where you can search for similar patients using text, images, and medical history, and predict future health risks years in advance – Apollo brings this closer to reality.
Injecting spatial transcriptomics data into existing pathology foundation models unlocks significant performance gains across a range of downstream tasks, including molecular status prediction and gene-to-image retrieval.
