🔬Breast Cancer Diagnostic Tool

Breast Cancer Classification

Enter patient measurements below to receive an AI-assisted diagnostic result powered by a clinically validated model.

Model: Logistic RegressionAccuracy: 97.37%Recall: 95.24%ROC-AUC: 0.9960

Patient Measurements

All 11 features are derived from digitized FNA (Fine Needle Aspirate) images of breast masses. Enter precise float values.

Mean concave portions of cell contour

Standard error of concave portions

Worst concave portions of contour

Mean severity of concave portions

Worst severity of concave portions

Mean distance from center to perimeter

Standard error of the radius

Worst local variation in radius lengths

Worst symmetry of the cell nucleus

Mean standard deviation of gray-scale values

Worst standard deviation of gray-scale values

Data is processed locally and not stored. Results are for screening assistance only.