Artificial intelligence (AI) is revolutionizing the treatment of Attention Deficit Hyperactivity Disorder (ADHD) through more precise diagnoses and personalized therapies. AI-based cognitive training programs utilize technologies such as augmented reality (AR) and virtual reality (VR) to enhance executive functions in children with ADHD, offering interactive and personalized exercises that stimulate attention and impulse control. These programs, including CogniFit, BrainBeat, NeuroPlus, and Lumosity, integrate real-time feedback and continuous monitoring, increasing motivation and treatment effectiveness. AI supports early diagnosis by analyzing data from neuropsychological, behavioral, and neurophysiological tests, identifying complex patterns associated with ADHD. Examples of diagnostic tools include QbTest, Adeo, NeuroElectrics, Mindstrong Health, and Cortica. However, despite promising results, it is necessary to scientifically validate these approaches and address challenges related to accessibility and data privacy protection. In conclusion, AI represents an innovative frontier in ADHD treatment, significantly improving patients' quality of life through personalized therapies and dynamic monitoring.
Artificial Intelligence in ADHD treatment: a brief narrative review
Alessandro Frolli
;Marco Romano
2024-01-01
Abstract
Artificial intelligence (AI) is revolutionizing the treatment of Attention Deficit Hyperactivity Disorder (ADHD) through more precise diagnoses and personalized therapies. AI-based cognitive training programs utilize technologies such as augmented reality (AR) and virtual reality (VR) to enhance executive functions in children with ADHD, offering interactive and personalized exercises that stimulate attention and impulse control. These programs, including CogniFit, BrainBeat, NeuroPlus, and Lumosity, integrate real-time feedback and continuous monitoring, increasing motivation and treatment effectiveness. AI supports early diagnosis by analyzing data from neuropsychological, behavioral, and neurophysiological tests, identifying complex patterns associated with ADHD. Examples of diagnostic tools include QbTest, Adeo, NeuroElectrics, Mindstrong Health, and Cortica. However, despite promising results, it is necessary to scientifically validate these approaches and address challenges related to accessibility and data privacy protection. In conclusion, AI represents an innovative frontier in ADHD treatment, significantly improving patients' quality of life through personalized therapies and dynamic monitoring.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.