Using WGS and NGS as input data, ARETEAI created a predictive algorithm with outstanding accuracy! Further improvement will be achieved by feeding the AI with more data. The most important part is that the best model is from our proprietary AI architecture, which we’ve been building for the past two years.
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With entire genomes at hand, scientists can pinpoint DNA fragments responsible for different cancers and predict patient responses to cancer treatments. However, the sheer volume of whole-genome data makes it difficult to encode the characteristics of genomic variants as features for machine learning algorithms.

