Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Real-time fall detection and prediction system using IMU sensors and machine learning algorithms. fall-detection-system/ ├── README.md # Project overview and quick start ├── LICENSE # MIT License ├── ...

Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...

Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods have shown ...

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a complex metabolic disorder and one of the leading causes of chronic liver disease worldwide. Current diagnostic tools, such as ...

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations ...

AI and ML are transforming forensic applications with e-nose systems, offering rapid, cost-effective analysis for volatile organic compounds. A 32-element MOS sensor array enhances e-nose forensic ...

Abstract: The older people are often at high risk of falling because of various factors like the age-related issues which affect their control over muscles or because of weakness due to age. There are ...