Traditional processes used to discover new materials are complex, time-consuming, and costly, often requiring years of ...

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...

After changing its name from Clawdbot to Moltbot to OpenClaw within days, the viral AI agent faces security questions and a growing prevalence of scammers and grifters.

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

Complex human diseases—such as cancer, neurodegenerative disorders, autoimmune conditions, cardiometabolic disease, and chronic inflammatory syndromes—arise ...

Abstract: This paper proposes a multi-label text classification algorithm based on causal relationships to address the current challenge of accurately capturing label correlations in multi-label text ...