Unveiling schizophrenia's neural and mental signatures with machine learning

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.
IEEE

A Dual Paradigm of Machine Learning and Deep Learning for Early Identification of Autism Spectrum Disorder in Children Using Facial Image Dataset

Abstract: Autism Spectrum Disorder (ASD) is a complex, lifelong developmental condition that influences how individuals perceive, process, and engage with the world around them. Early childhood ...
Frontiers

Cortical hemodynamic responses and deep learning models of emotional face processing in preschool children with autism spectrum disorder: a fNIRS study

Purpose: The purpose of the present study was to characterize cortical hemodynamic responses during emotional face processing in preschool children with autism spectrum disorder (ASD) using functional ...
Frontiers

Identification of tobacco leaf diseases using hyperspectral imaging and machine learning with SHAP interpretability analysis

1 College of Agronomy, Sichuan Agricultural University, Chengdu, China 2 Yibin Municipal Company of Sichuan Provincial Tobacco Corporation, Yibin, China Tobacco leaf diseases significantly affect ...
IEEE

VSAT: Variational Spectrum-Attention Transformer for Fault Diagnosis of Rotary Machine Monitoring

Abstract: The anomaly identification of vibration monitoring signals for rotating machinery supports fault diagnosis. The abnormal representation of the monitoring signals for rotating machinery ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...