Volume 18, No. 6, 2021

Genomic Markers and Machine Learning for Improving Ovarian Cancer Prognosis

Dr. Suman Kumar Swarnkar


Ovarian cancer is a significant health concern, often diagnosed at advanced stages, leading to limited treatment options and poor prognosis. Genomic biomarkers have the potential to revolutionize ovarian cancer prognosis by providing insights into tumor biology and personalized treatment strategies. This scientific research paper explores the discovery of genomic biomarkers for ovarian cancer prognosis using advanced machine learning algorithms. Leveraging high-throughput sequencing data and computational techniques, this study aims to identify robust biomarkers that can enhance prognostic accuracy, ultimately contributing to improved patient outcomes.

Pages: 9079-9086

Keywords: Ovarian cancer, Genomic biomarkers, Prognosis, Machine learning, High-throughput sequencing, Personalized medicine, Feature selection, Data preprocessing, Tumor biology.

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