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 ...
Nature

Survival Analysis Using Machine Learning Techniques

Recent progress in survival analysis has been driven by the integration of machine learning techniques with traditional statistical models, such as the Cox proportional hazards model. This synthesis ...
Electricity Forum

AI Fault Detection in Electrical Distribution Systems Using Waveform Analytics

AI fault detection uses waveform analytics and machine learning to identify early electrical failure signatures in distribution systems. Utilities gain predictive insight into incipient faults, asset ...
Linux Journal

Unlocking Data Science Potential Understanding Machine Learning and Data Analysis with JupyterLab

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...
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 ...
Security

Sensormatic Solutions adds Machine Learning to Shrink Analyzer

Sensormatic Solutions, the global retail solutions portfolio of Johnson Controls (JCI), continues to improve the capabilities of its cloud-based loss prevention (LP) application, Shrink Analyzer. The ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
Science Daily

Novel machine learning-based cluster analysis method that leverages target material property

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Science Daily

Researchers use machine learning to predict exercise adherence

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...