Electroencephalography (EEG) is capable of capturing the evocative neural information
within the brain. As a result, it has been increasingly used for identifying neurological …

Electroencephalogram (EEG) signals contain information about the brain's state as they
reflect the brain's functioning. However, the manual interpretation of EEG signals is tedious …

For depression diagnosis, traditional methods such as interviews and clinical scales have
been widely leveraged in the past few decades, but they are subjective, time-consuming …

The global prevalence of Major Depressive Disorder (MDD) is increasing at an alarming
rate, underscoring the urgent need for timely and accurate diagnoses to facilitate effective …

Today, depression is a psychological condition that affects many individuals globally and, if
untreated, can negatively impact one's emotions and lifestyle quality. Machine learning (ML) …

The computer-aided thorax disease diagnosis suffers from the existing noisy labels in large-
scale datasets. Especially, the fine-grained thorax images also show high inter-similarity …

Artificial intelligence models do not provide information about exactly how the predictions
are reached. This lack of transparency is a major drawback. Particularly in medical …

The reliable monitoring of the depth of anesthesia (DoA) is essential to control the
anesthesia procedure. Electroencephalography (EEG) has been widely used to estimate …

Background and purpose Diagnosis of depression is based on tests performed by
psychiatrists and information provided by patients or their relatives. In the field of machine …

Purpose: Monocyte/HDL cholesterol ratio (MHR) is a novel inflammatory marker that is used
as a prognostic factor for cardiovascular diseases and has been studied in many diseases …