International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 8, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

Use of Machine Learning in Genomic Biomarker Identification and Predicting Breast Cancer Metastasis - A Comparative Study

Author(s) Mr. Ameya Suhas Joshi
Country United States
Abstract Breast cancer has highest incidence in the world among all the cancers. Breast cancer also has very high rate of metastasis. Gene expression data can be analyzed for diagnoses and prognoses. Using machine learning models genomic biomarkers can be identified that predict metastasis. This information will be useful to develop appropriate treatment plan, take proactive steps to regularly monitor for metastasis and an early diagnosis. XGBoost and CNN machine learning algorithms were chosen to compare on their predictiveness to identify genomic biomarkers that are predictive of metastasis.
Keywords Breast cancer, Metastasis, Meachine Learning, XGBoost, CNN
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-10-13
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.57745

Share this