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By applying a logistic regression model to a real-world dataset, we can detect breast cancer and predict whether a tumor is benign (not breast cancer) or malignant (breast cancer) based on its characteristics. This model used 9 independent variables: Clump thickness, Uniformity of cell size, Uniformity of cell shape, Marginal adhesion, Single epithelial cell, Bare Nuclei, Bland chromatin, Normal nucleoli, and Mitoses. Logistic regression helps identify correlations between these variables and the tumor class (benign or malignant), using odds ratios and confidence intervals to aid decision-making.