Breast Cancer Diagnosis using Convolutional Neural Network

Researcher selected 569 instances from the Breast Cancer Repository websites. Using two input parameters, Benign and Malignant, we computed precision, recall, and F1-score employing neural network, support vector machine, Random Forest, and Nearest Neighbor models. Subsequently, we contrasted these results with those obtained from a convolutional network, revealing significantly higher values for precision, recall, and F1-score.