International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 2
March-April 2026
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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 |
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E-ISSN 2582-2160
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IJFMR DOI prefix is
10.36948/ijfmr
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