Machine learning projects aren’t just practice—they’re your ticket to proving skills, landing jobs, and staying relevant in a fast-changing AI world. From beginner-friendly models to complex, industry ...

Somewhere on Kaggle, the open data platform where anyone can upload a spreadsheet and call it a dataset, two files labeled as stroke and diabetes patient records became quietly popular. Researchers ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD than traditional tools. Heart failure is one of the most serious and ...

Chronic kidney disease (CKD) and heart failure (HF) share pathophysiological mechanisms, rendering HF one of the most burdensome cardiovascular complication in CKD. Current HF prediction models, ...

Recent research suggests that breast arterial calcification (BAC) picked up on routine mammograms may help predict a woman's risk of stroke, heart failure, and dying from a cardiac-related cause.

Cardiovascular disease (CVD) remains the foremost contributor to global illness and death, underscoring the critical need for effective tools that can predict risk at early stages to support ...

Stroke is one of the leading causes of death and disability worldwide, making early screening and risk prediction crucial. Traditional methods have limitations in handling nonlinear relationships ...

Abstract: Heart disease remains a leading cause of mortality worldwide, necessitating early and accurate detection to improve patient outcomes. This paper presents a Heart Disease Prediction System ...

Multiple Disease Prediction System using Machine Learning. Predicts Parkinson's, Heart Disease, and Diabetes via a web interface powered by Logistic Regression, SVM, KNN, and Stacking Ensemble.

Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.