A binary classification project using Logistic Regression on the Breast Cancer Wisconsin dataset. This project includes data preprocessing, model training, evaluation, and visual analysis using Python ...

This project demonstrates a complete pipeline for building a binary classifier using Logistic Regression on the Breast Cancer Wisconsin dataset.

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...

Impact of variant allele frequency (VAF) of TP53 alterations and Signatera circulating tumor DNA (ctDNA) monitoring for patients (pts) with advanced urothelial carcinoma (aUC) treated with enfortumab ...

ABSTRACT: Over the past ten years, there has been an increase in cardiovascular disease, one of the most dangerous types of disease. However, cardiovascular detection is a technique that analyzes data ...

ABSTRACT: Over the past ten years, there has been an increase in cardiovascular disease, one of the most dangerous types of disease. However, cardiovascular detection is a technique that analyzes data ...

Introduction: Sequencing and phylogenetic classification have become a common task in human and animal diagnostic laboratories. It is routine to sequence pathogens to identify genetic variations of ...

1 Agriculture and Agri-Food Canada, Sherbrooke Research and Development Centre, Sherbrooke, QC, Canada 2 Faculty of Science, Sherbrooke University, Sherbrooke, QC, Canada MAP employs complex ...