A Machine Learning Model that detects breast cancer by applying a logistic regression model on a real-world dataset and predict whether a tumor is benign (not breast cancer) or malignant (breast cancer) based off its characteristics.
This model can identify correlations between the following 9 independent variables and the class of the tumor (benign or malignant).
- Clump thickness
- Uniformity of cell size
- Uniformity of cell shape
- Marginal adhesion
- Single epithelial cell
- Bare Nuclei
- Bland chromatin
- Normal nucleoli
- Mitoses
Logistic regression can identify important predictors of breast cancer using odds ratios and generate confidence intervals that provide additional information for decision-making. Model performance depends on the ability of the radiologists to accurately identify findings on mammograms.