BioinformaticsJournal of Computational BiologyPeer-reviewed
A highly accurate model for screening prostate cancer using propensity index panel of ten genes
Shipra Jain, Kawal Preet Kaur Malhotra, Sumeet Patiyal, Gajendra P. S. Raghava
The paper develops a logistic regression model with a propensity index panel of ten genes to accurately screen prostate cancer, achieving 96.36% accuracy and 0.99 AUROC.
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