Machine Learning and ADHD Mental Health Detection - A Short Survey

This paper explores the current machine learning based methods used to identify Attention Deficit Hyperactivity Disorder (ADHD) in humans. With ADHD being one of the most prevalent mental health disorders worldwide, machine learning could be one of the effective solutions to objective diagnosis support to clinicians. We explore the use of machine learning with different sensing techniques such as functional Magnetic Resonance Imagery (fMRI) and Electroencephalography (EEG). Moreover, we also explore other approaches to detect ADHD such as computer based tasks, medical questionnaires and medical notes. With mental health awareness on the rise, it is necessary to survey the existing literature on ADHD for a machine learning based reliable Artificial Intelligence (AI). Which can aid clinicians in order to speed up the ADHD diagnosis process.