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September 5, 2025International Journal for Research in Applied Science and Engineering TechnologyOpen Access

Breast Tumor Classification Using Machine Learning (KNN) and Deep Learning (CNN)

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Authors

RAR AbinayaSri Venkateshwaraa Medical College Hospital and Research Centre

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Implication

This analysis employs K-Nearest Neighbor and Convolutional Neural Networks for breast tumor classification, suggesting AI can enhance diagnostic accuracy in ultrasound imaging.

Key Points

KNN and CNN are applied to classify breast tumors into benign and malignant categories.
The study evaluates both models on ultrasound images, achieving high performance metrics like accuracy and sensitivity.
KNN uses handcrafted features to establish a baseline, while CNN learns complex features automatically from images.
The findings highlight AI's potential in improving breast cancer diagnosis speed and consistency.

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R Abinaya (2025) studied this question.

synapsesocial.com/papers/68bb3efd2b87ece8dc957b7e https://doi.org/10.22214/ijraset.2025.73830

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Implication

This analysis employs K-Nearest Neighbor and Convolutional Neural Networks for breast tumor classification, suggesting AI can enhance diagnostic accuracy in ultrasound imaging.

Breast Tumor Classification Using Machine Learning (KNN) and Deep Learning (CNN)

Discussion

Member takes

Implication

Key Points

Cite This Study

Breast Tumor Classification Using Machine Learning (KNN) and Deep Learning (CNN)

Discussion

Member takes

Implication

Key Points

Cite This Study

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