Machine learning models identify key predictors of driving under the influence of alcohol or cannabis

The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary ...
News-Medical.Net

Using machine learning to identify individuals at risk for intimate partner violence

Researchers at Mass General Brigham have developed a series of artificial intelligence (AI) tools that uses machine learning to identify individuals who may be at risk for intimate partner violence ...
Tech Xplore on MSN

Facing the music: Detecting dangerous driving through AI facial analysis

Researchers from Edith Cowan University (ECU) are developing new technology that could change how drunk and dangerous drivers are identified. Using a single 3D deep learning model, researchers are ...
IEEE

Driver Drowsiness Detection Using Machine Learning and Computer Vision Techniques

Abstract: Driver drowsiness is a significant cause of road accidents, making early detection essential for improving traffic safety. This paper proposes a vision-based software system for detecting ...
Frontiers

Security of Drivers in Intelligent Transportation Systems: Privacy Preserving Federated Transfer Learning for Driver Drowsiness Detection

The final, formatted version of the article will be published soon. Driver drowsiness is a serious concern for road safety within intelligent transportation systems and it can reduce the safety and ...
IEEE

Single-Channel Wearable EEG Using Low-Power Qvar Sensor and Machine Learning for Drowsiness Detection

Abstract: This work deals with the fabrication and validation of an innovative wearable single-channel electroencephalogram (EEG) system, designed for real-time monitoring of specific brain activity.
Morningstar

Machine Learning Can Forecast Which Stock Factors Will Outperform

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
ahajournals.org

Abstract Fri013: AI-Driven Gait Classification for Peripheral Artery Disease (PAD) Detection Using Machine Learning and Nonlinear Gait Dynamics

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 ...
Scientific Research Publishing

Chirra, V., ReddyUyyala, S. and KishoreKolli, V. (2019) Deep CNN: A Machine Learning Approach for Driver Drowsiness Detection Based on Eye State.

ABSTRACT: This research presents a Driver Drowsiness Detection System (DDDS) that uses a Convolutional Neural Network (CNN) to improve road safety. The system uses a vast dataset of 97,860 images from ...