Artificial intelligence for multimodal data integration in oncology is a research paper published in Cancer Cell (2022). On theSindex it has a DataRank of 0. It has been cited 692 times.
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National Institute of General Medical Sciences
Grant: R35GM138216
National Institute of General Medical Sciences
Grant: T32CA251062
NHGRI NIH HHS
Grant: T32 HG002295
National Science Foundation
Siebel Scholars Foundation
National Institutes of Health
Brigham and Women's Hospital
National Cancer Institute
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Keywords
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Additional file 1 of TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
Additional file 1 of TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
Additional file 2 of TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
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Additional file 1 of Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication
Additional file 3 of TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology
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Additional file 2 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 1 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 2 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 4 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 4 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 3 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 3 of An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study
Additional file 1 of A systematic analysis of deep learning in genomics and histopathology for precision oncology
Additional file 1 of A systematic analysis of deep learning in genomics and histopathology for precision oncology