Challenge Cancer genomic medicine, in which therapeutic agents are selected based on a patient’s genetic mutation information, requires clinicians to search through vast amounts of medical data in order to develop ef fective treatment plans. Solution Fujitsu AI technology for information extraction and data integration was used to construct a system that enables candidate drugs to be quickly matched with genetic mutations in cancer tissue. Outcomes • Centralized access to drug information and clinical test data. • Significantly faster determination of potential drug ef ficacy and collation of supporting clinical data. • Improved therapeutic outcomes and avoidance of unnecessary treatments. Using Fujitsu AI technology for information extraction and graph structuring, Ai

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