Breast Cancer Detection System Using Machine Learning

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Shreyali Khobragade
Ishwar Sambhale
Atharv Mahajan
Dipannita Mondal

Abstract

AI is transforming the medical field, especially in the early detection and categorization of breast cancer. Deep learning models such as CNNI-BCC have shown remarkable accuracy in analyzing MRI scans to identify various types of breast cancer. This advancement in technology has significant implications for enhancing patient outcomes.


By utilizing AI, healthcare professionals can now receive more accurate. The high accuracy of CNNI-BCC in interpreting MRI scans supports the early detection of breast cancer, which plays a vital role in improving treatment outcomes. By highlighting abnormalities that might be overlooked by conventional techniques, this technology helps clinicians make more timely and effective decisions.

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How to Cite
Khobragade, S., Sambhale, I., Mahajan, A., & Mondal, D. (2025). Breast Cancer Detection System Using Machine Learning. International Journal on Advanced Computer Theory and Engineering, 14(1), 623–626. Retrieved from https://journals.mriindia.com/index.php/ijacte/article/view/612
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Articles

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