Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer's disease with nearly 93% accuracy.

As firms increasingly incentivize employees to build and oversee complex teams of agents—for example, by measuring and ...

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 ...

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 ...

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.

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 ...

This study explores the feasibility of using breathomic biomarkers analyzed by machine learning as a non-invasive diagnostic tool to differentiate between benign and malignant thoracic lesions, aiming ...

Netradyne, a global leader in AI-driven fleet safety, today announced the launch of its flagship Driver•i D-450 video safety platform and the latest DMS Sensor in India. The four-camera D-450 system – ...

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 the ...