“Explainable AI” for use in genomic medicine and cancer treatment planning
Fujitsu announced the development of explainable AI technology that automatically draws on data in multiple formats, including text, images, and numerical data, to create knowledge graphs that will help users to more easily draw meaning from large-scale data sets with high accuracy for areas including medicine
To confirm the effectiveness of this technology, Fujitsu tested it on several key benchmarks from the medical field, including for lung cancer type classification and breast cancer patient survival prediction. These tests confirmed that Fujitsu’s technology can accurately support the identification of two main types of lung cancer, for example, by illuminating the factors behind the pathological classification based on key visual cues.
Fujitsu has also developed a technology to extract and train algorithms on the distinct features of images with completely different depictions of objects and to make highly accurate judgments. It is anticipated that this technology can be applied to train AI to support highly accurate assessments from pathological images for which sufficient training data cannot be prepared.
Going forward, Fujitsu will continue to develop these multimodal technologies for general use in a range of different fields and disciplines. By the end of fiscal 2024, Fujitsu also plans to offer the newly developed technologies via the Fujitsu Research Portal, an environment that gives users the ability to quickly test Fujitsu’s advanced technologies.
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