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Diagnostic du cancer du sein avec l’algorithme des K PLUS proches voisin (KNN)

Présenté par

Directed by: Samira Mohammadi
Supervised by: Prof. Yacine Yaddaden


This project proposes a computer-aided diagnosis for breast cancer using the K-Nearest Neighbor (KNN) algorithm. The goal is to develop a reliable and efficient diagnostic tool that can identify breast cancer at an early stage. The KNN algorithm is implemented using the Sharp C programming language, with model performance evaluation using a test data set. The results show that the accuracy of the KNN model strongly depends on the value of K, with a maximum accuracy of 90.71% for K=9. Further studies are needed to optimize this value and evaluate the performance of the algorithm on larger data sets.

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