The Cancer Genome Atlas
PulseAugur coverage of The Cancer Genome Atlas — every cluster mentioning The Cancer Genome Atlas across labs, papers, and developer communities, ranked by signal.
3 天有情绪数据
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GLP-1 drugs may reduce cancer progression, new study suggests
New research presented at the American Society of Clinical Oncology meeting suggests that GLP-1 medications, commonly used for diabetes and weight loss, may also reduce the progression of certain cancers. A study analyz…
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ProtoPathway integrates imaging and genomics for cancer survival prediction
Researchers have developed ProtoPathway, a novel multimodal framework designed for predicting cancer survival. This framework integrates whole slide imaging and transcriptomics data by using biologically grounded repres…
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New HDMoE framework enhances cancer survival prediction with multimodal data
Researchers have developed a new framework called HDMoE to improve multimodal cancer survival prediction. This hierarchical decoupling-fusion mixture-of-experts approach aims to better integrate data from sources like w…
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PPI-Net model links protein interactions to disease processes
Researchers have developed PPI-Net, a novel graph neural network designed to connect protein interactions with functional disease processes. This hierarchical model integrates protein-protein interaction networks with p…
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New Bayesian tree ensemble model tackles high-dimensional causal survival analysis
Researchers have introduced a new Bayesian tree ensemble model designed for causal survival analysis in high-dimensional settings. This model utilizes a horseshoe prior on step heights to achieve adaptive shrinkage, all…
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Foundation models show modest gains for whole-slide image retrieval in cancer data
A new study published on arXiv evaluates ten different pipelines for whole-slide image retrieval in cancer pathology data. The research found that while the TITAN foundation model performed best, its advantage over patc…
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Foundation models show promise in classifying atypical mitosis in cancer research
Researchers have benchmarked deep learning and vision foundation models for classifying atypical versus normal mitosis, a crucial indicator of tumor malignancy. The study evaluated end-to-end trained models, linear prob…
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ASTRA framework unifies pathology foundation models for cancer recognition and localization
Researchers have developed ASTRA, a new framework designed to unify fragmented representations from various pathology foundation models into a cohesive slide-level understanding. This system semantically grounds these r…
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PathMoG neural network improves cancer survival prediction using multi-omics data
Researchers have developed PathMoG, a novel graph neural network designed for predicting cancer survival rates using multi-omics data. The model organizes genetic information into pathway modules and uses a hierarchical…