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 ...
Unite.AI

Why Data Labeling Is Critical to Building Accurate Machine Learning Models

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...
InfoWorld

Machine learning: The deplorable state of deployment

We’ve gotten pretty good at building machine learning models. From legacy platforms like SAS to modern MPP databases and Hadoop clusters, if you want to train up regression or classification models, ...
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 ...
Frontiers

Brain-Computer Interfaces (BCIs) for daily activities: Innovations in EEG signal analysis and machine learning approaches

Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human brain and external devices. With recent advancements in Electroencephalography ...
Analytics Insight

Top Online Resources to Learn Data Science in 2026

Overview: Structured online platforms provide clear, step-by-step learning paths for beginners.Real progress in data science comes from hands-on projects and co ...