Advanced machine learning framework for enhancing breast cancer diagnostics through transcriptomic profiling

Abstract Purpose This study proposes an advanced machine learning (ML) framework for breast cancer diagnostics by integrating transcriptomic profiling with optimized feature selection and classification techniques. Materials and methods A dataset of 1759 samples (987 breast cancer patients, 772 heal...

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Bibliographic Details

Published in:	Discover Oncology
Main Authors:	Mohamed J. Saadh, Hanan Hassan Ahmed, Radhwan Abdul Kareem, Anupam Yadav, Subbulakshmi Ganesan, Aman Shankhyan, Girish Chandra Sharma, K. Satyam Naidu, Akmal Rakhmatullaev, Hayder Naji Sameer, Ahmed Yaseen, Zainab H. Athab, Mohaned Adil, Bagher Farhood
Format:	Article
Language:	English
Published:	Springer 2025-03-01
Subjects:	Breast cancer Machine learning Transcriptomic profiling Feature selection Predictive modeling Biomarkers
Online Access:	https://doi.org/10.1007/s12672-025-02111-3