Alzheimer's and related diseases are significant health issues of this era. The
interdisciplinary use of deep learning in this field has shown great promise and gathered …

Early detection is the key to successfully tackling dementia, a neurocognitive condition
common among the elderly. Therefore, screening using technological platforms such as …

Cardiovascular disease is the leading cause of death in the world. It is vital to prevent it by
rapid diagnosis and appropriate management through periodic blood pressure (BP) …

Recently, artificial intelligence (AI) has been one of the hottest topics in the technological
world. Although it is involved in many domains, it was recently involved in the healthcare …

A variety of tools and methods have been used to measure behavioral symptoms of attention-
deficit/hyperactivity disorder (ADHD). Missing data is a major concern in ADHD behavioral …

Learning classifiers with imbalanced data can be strongly biased toward the majority class.
To address this issue, several methods have been proposed using generative adversarial …

Background Attention deficit hyperactivity disorder (ADHD) is a well-studied topic in child
and adolescent psychiatry. ADHD diagnosis relies on information from an assessment scale …

Objective Much has been invested in big data analytics to improve health and reduce costs.
However, it is unknown whether these investments have achieved the desired goals. We …

As technology advances, diagnostic tests continue to improve and each year, we are
presented with new alternatives to standard procedures. Given the plethora of diagnostic …

Objective: This paper proposes a multiclass deep learning method for the classification of
dementia using an informant-based questionnaire. Methods: A deep neural network …