Tag: Machine learning

AIScienceTechnology

AI Models Achieve Over 98% Accuracy in Predicting Mental Health Conditions Using Psychometric Data

Artificial intelligence systems have demonstrated exceptional capability in identifying depression, anxiety, and stress disorders according to new research. The study utilized validated psychometric data from nearly 40,000 participants to train multiple machine learning models, with support vector machines achieving accuracy rates exceeding 98% across all three conditions.

Breakthrough in Mental Health Prediction

Artificial intelligence systems have demonstrated remarkable accuracy in predicting common mental health conditions using standardized psychological assessments, according to recent research published in Scientific Reports. The study, which analyzed responses from 39,775 participants, indicates that machine learning algorithms can identify depression, anxiety, and stress with accuracy rates exceeding 98% using the Depression Anxiety Stress Scales-42 (DASS-42) questionnaire combined with demographic information.

by Julian Trent
EngineeringScienceTechnology

Industrial Waste Transforms Concrete: Red Mud and Recycled Aggregates Boost Sustainability

Scientists report that incorporating industrial waste products into concrete formulations significantly improves material performance while addressing environmental concerns. Advanced machine learning models now enable precise prediction of concrete properties, accelerating sustainable construction innovation.

Breakthrough in Sustainable Construction Materials

Construction industry researchers have developed an innovative approach to concrete production that simultaneously addresses waste management challenges and improves material performance, according to recent findings published in Scientific Reports. The study demonstrates how industrial byproducts can effectively replace traditional concrete components while maintaining or even enhancing structural properties.

by Julian Trent
AIScienceTechnology

Satellite Mapping Reveals Vast Scale of Tropical Mining Operations

Researchers have created the most comprehensive map of tropical mining operations using machine learning and high-resolution satellite imagery. The dataset reveals mining activities covering approximately 66,400 square kilometers annually across tropical regions worldwide.

Breakthrough in Mining Monitoring

Scientists have developed a comprehensive mapping system that reveals the extensive footprint of mining operations across tropical regions worldwide, according to a new report published in Nature Sustainability. The research team utilized advanced machine learning algorithms trained on thousands of mining sites to automatically identify and map extraction areas using high-resolution satellite imagery.

by Darren Holt