Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Early Detection and Classification of Breast Cancer Using ML

Early Detection and Classification of Breast Cancer Using ML

Nagaraju, C.
Narasimhaiah, P.

Paperback

Medical Reference

ISBN10: 620957503X
ISBN13: 9786209575037
Publisher: LAP Lambert Academic Publishing
Published: Feb 6 2026
Pages: 120
Weight: 0.38
Height: 0.28 Width: 6.00 Depth: 9.00
Language: English
The most common cancer among the women in the world with high mortality rate is breast cancer. Early detection and accurate classification of breast cancer are essential for improving patient survival and enabling timely clinical intervention. Machine learning techniques have been widely applied to analyze diagnostic data from mammography, ultrasound, magnetic resonance imaging, and histopathological examinations. Traditional machine learning methods use handcrafted features classified by algorithms such as Support Vector Machines and Random Forests, while deep learning models, particularly convolutional neural networks, automatically learn discriminative feature representations from raw data. Experimental studies show that these models can effectively distinguish between benign and malignant lesions with high accuracy, supporting radiologists in early-stage diagnosis.

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