The rapid development of biosensing technologies together with the advent of deep learning
has marked an era in healthcare and biomedical research where widespread devices like …

Background Electroencephalography (EEG) is a supplementary diagnostic tool in psychiatry
but lacks practical usage. EEG has demonstrated inconsistent diagnostic ability because …

Background Major depressive disorder (MDD) has a high incidence and an unknown
mechanism. There are no objective and sensitive indicators for clinical diagnosis. Objective …

ABSTRACT Ethnopharmacological relevance Rehmannia glutinosa Libosch.(RGL) is a
famous ethnic medicine contained in antidepressant Chinese Medicine formulas and is …

Background Mood disorders and schizophrenia affect millions worldwide. Currently,
diagnosis is primarily determined by reported symptomatology. As symptoms may overlap …

Numerous existing studies on machine learning-based depression recognition have
focused on the frequency domain features of EEG data. Furthermore, their experiments have …

Psychological disorders have increased globally at an alarming rate. Among these
disorders, depression stands out as one of the leading and most prevalent conditions that …

Depression has become the prevailing global mental health concern. The accuracy of
traditional depression diagnosis methods faces challenges due to diverse factors, making …

In this day and age, depression is still one of the biggest problems in the world. If left
untreated, it can lead to suicidal thoughts and attempts. There is a need for proper …

Depression, a paramount global health challenge, necessitates an advanced diagnostic
approach. This study employs EEG and AI on a psycho-physiological Healthy Brain Network …