Machine learning Analysis to Accurately Predict Tumor Type
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Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type

Highlights

  • CUP occurs in as many as 3–5% of patients when standard diagnostic tests are not able to determine the origin of cancer.
  • MI GPSai (Genomic Prevalence Score) is an AI that uses genomic and transcriptomic data to elucidate tumor origin.
  • The algorithm was trained on molecular data from 57,489 cases and validated on 19,555 cases.
  • MI GPSai predicted the tumor type out of 21 options in the labeled data set with an accuracy of over 94% on 93% of cases.
  • When also considering the second highest prediction, the accuracy increases to 97%.

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