A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Finding the right book can make a big difference, especially when you’re just starting out or trying to get better. We’ve ...

A one-day short course presented at the American Meteorological Society (AMS) Annual Meeting 2026 106th AMS Annual Meeting - Houston, TX January 25, 2026 at 8:30 AM - 3:45 PM Central Time (Hybrid) ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Google Colab is a really handy tool for anyone working with machine learning and data stuff. It’s free, it runs in the cloud, and it lets you use Python without a lot of fuss. Whether you’re just ...

Electrical power systems engineers need practical methods for predicting solar output power under varying environmental conditions of a single panel. By integrating an Arduino-based real-time data ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

By effectively integrating machine learning and logical reasoning in a balanced loop, coupled with engineering optimizations, ABLkit demonstrates superior performance in terms of predictive accuracy, ...