Predictive AI Model to Manage Transcriptomics-Based Transition of Hormone-Naive to Castrate-Resistant Prostate Cancer: An Opportunity Towards Precision Medicine

Abstract

Precision medicine is a groundbreaking approach to the treatment of prostate cancer. It involves tailoring medical decisions and therapies to individual patients based on their unique genetic makeup, lifestyle, and environmental factors. By analysing a patient's genetic profile, doctors can identify specific genetic alterations that drive the development and progression of prostate cancer. This knowledge allows for the selection of targeted therapies that directly address the underlying molecular abnormalities, increasing treatment efficacy and minimizing side effects. Precision medicine in prostate cancer offers the potential for more personalized and effective treatments, ultimately improving patient outcomes and quality of life. Hence, the study developed a highly accurate Convolutional Neural Network-1Dimensional (CNN) -1D model to predict the different pathological stages of PCa and castrate-resistant prostate cancer/Hormone resistant using a dataset generated on Affymetrix GeneChip Human Transcriptome Array 2.0 with accuracy of 0.98.