HIGHLIGHTS
- who: Revised et al. from the Artificial Intelligence Laboratory, Fujitsu Research, Fujitsu Ltd, Kawasaki, Kanagawa, Japan The University of Tokyo, Tokyo, Japan have published the Article: Explainable AI for Estimating Pathogenicity of Genetic Variants Using Large-Scale Knowledge Graphs, in the Journal: Cancers 2023, 15, 1118. of /2023/
- what: The authors propose AI to solve this problem and report the results of its application in identifying disease-causing variants. Methods: To assist physicians in their task of identifying disease-causing variants the authors propose an explainable AI (XAI) that combines high estimation accuracy with explainability . . .
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