The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
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 ...
Devdiscourse

From disease detection to biomass forecasting: AI improves aquaculture risk strategy

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...
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 ...
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 ...

Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
Tech Xplore on MSN

AI-guided micromachining advances next-generation biocompatible titanium alloys

Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of a next-generation biocompatible titanium alloy, potentially improving the ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...