Individualized prediction models in ADHD: a systematic review and meta-regression

G Salazar de Pablo, R Iniesta, A Bellato, A Caye… - Molecular …, 2024‏ - nature.com
There have been increasing efforts to develop prediction models supporting personalised
detection, prediction, or treatment of ADHD. We overviewed the current status of prediction …

A systematic review on the application of machine learning models in psychometric questionnaires for the diagnosis of attention deficit hyperactivity disorder

L Caselles‐Pina, A Quesada‐López… - European Journal of …, 2024‏ - Wiley Online Library
Attention deficit hyperactivity disorder is one of the most prevalent neurodevelopmental
disorders worldwide. Recent studies show that machine learning has great potential for the …

[HTML][HTML] The Potential of AI-Powered Face Enhancement Technologies in Face-Driven Orthodontic Treatment Planning

J Tomášik, M Zsoldos, K Majdáková, A Fleischmann… - Applied Sciences, 2024‏ - mdpi.com
Featured Application AI-powered face enhancement technologies have found their role in
orthodontic treatment planning. Our study has shown that AI is able to modify face pictures in …

Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques

RH Ali, WH Abdulsalam - Iraqi Journal of Science, 2024‏ - ijs.uobaghdad.edu.iq
Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting
millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and …

[HTML][HTML] Constructing features for screening neurodevelopmental disorders using grammatical evolution

EI Toki, G Tatsis, J Pange, IG Tsoulos - Applied Sciences, 2023‏ - mdpi.com
Featured Application This study is part of an ongoing research project titled “Smart
Computing Models, Sensors, and Early diagnostic speech and language deficiencies …

Advancements in Conversational AI: Building Mental Health Chatbot with BERT Model

K Mishra, H Bodkhe, R Naik… - … for Innovations in …, 2023‏ - ieeexplore.ieee.org
A significant portion of individuals experience various mental health challenges, including
depression, anxiety, stress, and more. Many people may choose not to consult a counsellor …

The Pros and Cons of Using Machine Learning and Interpretable Machine Learning Methods in psychiatry detection applications, specifically depression disorder: A …

H Simchi, S Tajik - arxiv preprint arxiv:2311.06633, 2023‏ - arxiv.org
The COVID-19 pandemic has forced many people to limit their social activities, which has
resulted in a rise in mental illnesses, particularly depression. To diagnose these illnesses …

The emerging role of artificial intelligence in the diagnosis and treatment of autism spectrum disorder and attention-deficit/hyperactivity disorder

M Nasrallah, A El Moghrabi, M Kayal… - International Journal …, 2025‏ - Taylor & Francis
Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are
neurodevelopmental disorders known to severely affect social and cognitive functions. ASD …

Exploring teachers' experiences in addressing ADHD during the post-pandemic transition

JM Suaybaguio, J Bernardo, JJ Serra… - E-Learning and …, 2024‏ - journals.sagepub.com
This study delves into how teachers are managing and teaching ADHD students during the
aftermath of the COVID-19 pandemic. Through interviews and observations from throughout …