Comparison Logistic Regression and Discriminant Analysis in classification groups for Breast Cancer

Using Classic Discriminant Analysis and Detection Function for Separation of Chemical Victims in Sardasht City to Exposed and Non Exposure Mustard Groups in 2013 and Comparison with Logistic Regression

Logistic discriminant analysis of breast cancer using ultrasound measurements

Background: Logistic discriminant method was applied to differentiate malignant from benign in a group of patients with proved breast lesions on the basis of ultrasonic parameters. Materials and Methods: Our database include 273 patients' ultrasonographic pictures consisting of 14 quantitative variables. The measured variables were ultrasound propagation velocity, acoustic impedence and attenua...

Comparison of logistic regression and neural network models in predicting the outcome of biopsy in breast cancer from MRI findings

Background: We designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the Artificial Neural Network (ANN). Materials and methods: The ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. Each patient’s record consisted of 6 subjec...

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

  Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population.   Methods : In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were ...

مقایسه دقت پیش‌بینی رگرسیون لجستیک و درخت رده‌بندی در تعیین عوامل خطر و پیش‌بینی ابتلا به سرطان پستان

Background and Objectives: Breast cancer is one of the most common malignancies in women which accounts for the highest number of deaths after lung cancer. The aim of the current study was to compare the logistic regression and classification tree models in determining the risk factors and prediction of breast cancer. Methods: We used from the data of a case-control study conducted on 303 pa...