Breast Cancer Detection Using Machine Learning Techniques - mohamad, mohamad (Latakia University Journal -Engineering Sciences Series, 2025)
Breast cancer affects approximately 10% of women worldwide at some point in their lives and has emerged as one of the most feared and prevalent cancers among women. The main dilemma arises when cancer cannot be properly detected in its early stages. Machine learning has proven to play a vital role in diagnosing diseases such as cancers. Effective methods for classification and data recognition are particularly essential in the medical field. In this project, classification techniques were employed using the PCA-KNN algorithm on the Wisconsin Breast Cancer Dataset. The main objective was to evaluate the accuracy of data classification concerning the efficiency and effectiveness of the PCA-KNN algorithm in terms of precision, recall, specificity, and the F1 score. The experimental results demonstrated an accuracy of up to 99%.