Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Acquiring labeled data for deep learning tasks such as medical image classification is a notoriously expensive and time-consuming process, often requiring expert-level annotation. The scarcity of high ...

Objective: To evaluate and to compare machine learning models for predicting hypertension in patients with diabetes using routine clinical variables. Methods: Using Behavioral Risk Factor Surveillance ...

The new Instagram feature reveals what the algorithm thinks you like and lets you adjust it, reshaping how content gets recommended on Reels. Instagram launched Your Algorithm in the U.S. today, a ...

In 2025, the Instagram algorithm has become more advanced than ever, using artificial intelligence and machine learning to decide what content users see in their Feeds, Reels, Stories, Explore pages, ...

ABSTRACT: Atrial fibrillation (AF) is a leading cardiac arrhythmia associated with elevated mortality risk, particularly in low-resource settings where early risk stratification remains challenging.

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...