Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability
to explain the complex decision-making process of machine learning (ML) and deep …

Mental health has become a major concern in recent years. Social media have been
increasingly used as platforms to gain insight into a person's mental health condition by …

Overfitting is a common issue in machine learning-based depression detection model.
Overfitting occurs when a machine learning model uses garbage data in the training …

A major psychological problem that numerous new mothers experience is postpartum
depression (PPD). A woman's capacity to care for herself and her child may be hampered by …

The entire world has been affected by the outbreak of COVID-19 since early 2020. Human
carriers are largely the spreaders of this new disease, and it spreads much faster compared …

The increasing prevalence of mental disorders among youth worldwide is one of society's
most pressing issues. The proposed methodology introduces an artificial intelligence-based …

Background The proliferation of social media platforms has provided a unique space for
discourse on mental health, originally intended to destigmatize mental illness. However …

The research describes an effective deep learning-based, data-centric approach for
diagnosing autism spectrum disorder from facial images. To classify ASD and non-ASD …

Epileptic seizure (ES) detection is an active research area, that aims at patient-specific ES
detection with high accuracy from electroencephalogram (EEG) signals. The early detection …

Stress is a condition that causes a specific physiologicsal response. Heart rate variability
(HRV) is a critical aspect in identifying stress. It is crucial for those who want to keep track of …