Publication

1134P Personalized medicine in advanced breast cancer: AI-driven genomic test for CDK4/6 treatment response prediction

P. Zawadzki, A. Wozna, P. Sztromwasser, W. Majer-Burman, R. Stepien, K. Pacewicz, D. Sielski, M. Gniot M. Wojtaszewska, M. Dabrowski, M. Piernik

Published
September 1, 2021
journal
DOI
https://doi.org/10.1016/j.annonc.2021.08.776
WGS
Structural Variants
Machine Learning
Biomarkers
AI

The Random Forest-based AI algorithm achieved good performance on nine genomic features that were selected as the most biologically relevant.

Hold-out validation, a performance metric of the CDK4/6iDx classifier, provided a discriminative power of 83.88% by area under receiver operating characteristic (AUROC) curve analysis. Consistently, the low rate of misclassifications (high precision and recall of 90% and 88%, respectively) demonstrates the high discriminating power of the final classifier algorithm.

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1134P Personalized medicine in advanced breast cancer: AI-driven genomic test for CDK4/6 treatment response prediction
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