Knowridge Science Report

A new way to predict survival in older heart failure patients

A research team from Juntendo University in Japan wanted to find a better way to predict survival for older people with heart failure. The project was led by Professor Tetsuya Takahashi, Assistant ...

Physical function is a crucial predictor of survival after heart failure, mortality risk model indicates

Monitoring and treating heart failure (HF) is a challenging condition at any age. Several models, such as Atrial fibrillation, Hemoglobin, Elderly, Abnormal renal parameters, Diabetes mellitus (AHEAD) ...
European Medical Journal

AI Model Predicts Cardiac Tamponade During Ablation

A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve ...
Frontiers

Beyond just correlation: causal machine learning for the microbiome, from prediction to health policy with econometric tools

The human microbiome is increasingly recognized as a key mediator of health and disease, yet translating microbial associations into actionable interventions remains challenging. This review ...
IEEE

Heart disease prediction using machine learning and data analytics approach

Abstract: In recent times, Machine Learning has played a significant role in the healthcare industry and amongst all of the major diseases, heart disease is one of the significant and most critical ...
IEEE

Heart Disease Prediction Using Machine Learning

Abstract: The heart plays a pivotal role in the functioning of living organisms, making its diagnosis and prediction of related diseases a matter of utmost importance. Approximately 17.9 million ...
BMJ

Machine learning methods, applications and economic analysis to predict heart failure hospitalisation risk: a scoping review

Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...