Predicting Mutational Status of Driver and Suppressor Genes Directly from Histopathology With Deep Learning: A Systematic Study Across 23 Solid Tumor Types

Chiara Maria Lavinia Loeffler*, Nadine T Gaisa, Hannah Sophie Muti, Marko van Treeck, Amelie Echle, Narmin Ghaffari Laleh, Christian Trautwein, Lara R Heij, Heike I Grabsch, Nadina Ortiz Bruechle, Jakob Nikolas Kather

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Article number806386
Number of pages13
JournalFrontiers in Genetics
Volume12
DOIs
Publication statusPublished - 16 Feb 2022

Keywords

  • deep learning
  • artificail intelligence (AI)
  • cancer pathway
  • cancer pathway genes
  • genetic
  • TCGA
  • COMPREHENSIVE MOLECULAR CHARACTERIZATION
  • INTEGRATED GENOMIC CHARACTERIZATION
  • SIGNALING PATHWAYS
  • LANDSCAPE

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