Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

AI Stock Trading: The Future of Algorithms in Investing

According to Mercer's 2024 AI in Investment Management global manager survey, 91% of asset managers either currently use AI (54%) or plan to use it within their investment strategy or asset-class ...
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 risk stratification.
IEEE

Federated Function-on-function Regression with an Efficient Gradient Boosting Algorithm for Privacy-Preserving Telemedicine

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...
Frontiers

Explainable machine learning for stroke risk prediction: a comparative study with SHAP-based interpretation

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 ...
Medical Xpress

Boosting Machine Learning Algorithms

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.
C&EN

PI3K-Seeker: A Machine Learning-Powered Web Tool to Discover PI3K Inhibitors

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Phosphatidylinositol 3-kinases (PI3Ks) play a crucial role in human metabolism, and ...
ahajournals.org

Abstract 4340723: Comparative Study of Coronary Artery Disease (CAD) Prediction: Conventional QRISK3 vs. Enhanced Machine Learning Models Combined with Particle Swarm ...

Background: Coronary Artery Disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known ...
ahajournals.org

Abstract 4371610: Boosting Prediction: Machine Learning Models Outperform Traditional Risk Scores for Primary Cardiovascular Prevention

Background: Standard CVD risk calculators assume linear relationships among risk factors. ML methods (gradient boosting, random forests, neural networks, support vector machines) capture nonlinear ...
Scientific Research Publishing

Saied, M., Guirguis, S. and Madbouly, M. (2023) A Comparative Study of Using Boosting-Based Machine Learning Algorithms for IoT Network Intrusion Detection. International ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Forbes

Learning The Most Rigorous Approaches To Validating Algorithms And Greatly Boosting AI Safety

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the importance of performing ...