| Abstrakt: |
A recent study conducted by a Doctoral School in Mumbai, India, explores the use of machine learning and deep learning techniques for the early detection of Attention-Deficit/Hyperactivity Disorder (ADHD) in children. The researchers highlight the challenges in detecting ADHD and the potential of electroencephalogram (EEG) data classification techniques. They discuss the use of machine learning and artificial intelligence strategies in identifying ADHD based on EEG signals, as well as the potential of deep learning algorithms, particularly convolutional neural networks (CNN), in overcoming these challenges. The study concludes that EEG has been used to study ADHD neurological connections, and advancements in deep learning algorithms are expected to further enhance ADHD detection. [Extracted from the article] |
