Abstract: Speech analysis can be employed in real-time to detect emotions using machine learning. Emotions can be identified by analysing features such as pitch, intensity, and spectral patterns.

DC arc fault detection is undergoing a transformation thanks to edge AI, helping power systems spot dangerous faults faster, ...

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 ...

A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types in patients with cancers of unknown primary (CUP), according to research ...

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

As the use of artificial intelligence across medicine increases nationwide, The Daily Pennsylvanian spoke to professors, doctors, and researchers at the Perelman School of Medicine about how they are ...

The SVM identified loss of appetite, flank discomfort, abdominal bloating or gurgling, and pale or yellowish complexion as the most discriminative features. Unsupervised clustering revealed four ...

Abstract: This project addresses the critical need for safeguarding patterns identified in datasets during their transmission to a destination. The process involves two key steps: first, employing ...