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Predicting tumour mutational burden from histopathological images using multiscale deep learningDOI 10.1038/s42256-020-0190-5
Predicting tumour mutational burden from histopathological images using multiscale deep learningSemantic proximity
Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.Semantic proximity
Predicting Tumor Mutational Burden From Lung Adenocarcinoma Histopathological Images Using Deep LearningSemantic proximity
Pan-cancer computational histopathology reveals mutations, tumor composition and prognosisSemantic proximity
Predicting Mutational Status of Driver and Suppressor Genes Directly from Histopathology With Deep Learning: A Systematic Study Across 23 Solid Tumor TypesSemantic proximity
Pan-cancer image-based detection of clinically actionable genetic alterations.Semantic proximity
Predicting gastric cancer tumor mutational burden from histopathological images using multimodal deep learning.Semantic proximity
Predicting cancer outcomes from histology and genomics using convolutional networksSemantic proximity
DeepMed: A unified, modular pipeline for end-to-end deep learning in computational pathologySemantic proximity
Deep learning links histology, molecular signatures and prognosis in cancerSemantic proximity
Pan-cancer integrative histology-genomic analysis via multimodal deep learningSemantic proximity
A Deep Learning solution for triaging patient with cancer from their predicted mutational status using histopathological imagesSemantic proximity
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