Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
GitHub

APR Mini Project on SVM and SVR

In this project, We build a Support Vector Machines classifier to classify a Pulsar star. We have used the Predicting a Pulsar Star dataset for this project. We have downloaded this dataset from the ...
IEEE

FASTEN: Fuzzy Neural Support Vector Machine for Classification

Abstract: Classification tasks have long been a central concern in the field of machine learning. Although deep neural network-based approaches offer a novel, versatile, and highly precise solution ...
Scientific Research Publishing

Zhu, W., Song, Y. and Xiao, Y. (2020) Support Vector Machine Classifier with HUberized Pinball Loss. Engineering Applications of Artificial Intelligence, 91, Article ID: 103635.

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...
ascopubs.org

Impact of Tumor Location on Predicting Early-Stage Breast Cancer Patient Survivability Using Explainable Machine Learning Models

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...
Scientific Research Publishing

Research on Credit Risk Rating of Commercial Banks Based on Support Vector Machine

In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...
IEEE

Manifold Energy Projection Twin Support Vector Machine for Semi-Supervised Classification

Abstract: The Projection Twin Support Vector Machine (PTSVM) and its variant, the Least Squares PTSVM (LSPTSVM), have demonstrated significant effectiveness in supervised classification tasks due to ...