Pathogenicity prediction of gene fusion in structural variations: a knowledge graph-infused explainable artificial intelligence (xai) framework

HIGHLIGHTS

• What: As ChimerDriver outperformed the other four models , the authors focused the comparison exclusively on ChimerDriver. The model was trained on these datasets, and two types of evaluations were conducted as follows:
• Who: Katsuhiko Murakami and colleagues from the Computing Laboratories, Fujitsu Research, Fujitsu Ltd, Kawasaki, Kanagawa, Japan Division of Hematopoietic Disease Control, The Institute of Medical Science, The University of Tokyo have published the article: Pathogenicity Prediction of Gene Fusion in Structural Variations: A Knowledge Graph-Infused Explainable Artificial Intelligence (XAI) Framework, in the Journal: Cancers 2024, 1915 of /2024/
• How: To . . .
  

   

  

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