A confusion matrix for a cancer classification predictive model. Data practitioners can use the numbers derived from a confusion matrix to calculate their logistic regression models’ accuracy ...

Machine learning (ML) models have been increasingly used in clinical oncology for cancer diagnosis ... labels and binary labels by linear regression and logistic regression, respectively.

An additional assumption for multiple linear regression is that of no collinearity between the explanatory variables, meaning they should not be highly correlated with each other to allow reliable ...

Logistic regression analysis provided ORs with 95% CIs (crude and adjusted) for the likelihood of responder status (primary outcome), according to the study exposure (exercise Intervention vs Control) ...

Table 2 Modified Logistic-Regression Prediction Model (PLCO M2012) of Cancer Risk for 36,286 Control Participants Who Had Ever Smoked. Accuracy of Lung-Cancer Classification According to ...