• Dr. Shaik Khaleel Ahamed
• MohammedMuneebuddin
• Mohammed Wali Uddin Qureshi
• Mohammed Bilal

Breast cancer, a leading cause of mortality among women globally, necessitates early detection for improved outcomes. Machine learning (ML) techniques offer robust solutions by analyzing medical data, enhancing screening accuracy, and personalizing diagnoses based on genetic and lifestyle factors. ML aids in predicting cancer progression, assessing individual risk, and reducing false positives/negatives, minimizing unnecessary procedures. This integration underscores technology's transformative potential in healthcare, promising heightened accuracy, efficiency, and personalized care, ultimately improving patient outcomes and survival rates

ENSEMBLE,RF,BAGGING,accuracy,precision,recall,F1-score.

"ALGINTE: EMPOWERING EARLY DETECTION OF BREAST CANCER THROUGH MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.h784-h792, July-2024, Available :http://www.jetir.org/papers/JETIR2407787.pdf

"ALGINTE: EMPOWERING EARLY DETECTION OF BREAST CANCER THROUGH MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. pph784-h792, July-2024, Available at : http://www.jetir.org/papers/JETIR2407787.pdf