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Early Detection Of ADHD Among Children Using Machine Learning

Early detection of attention-deficit/hyperactivity disorder (ADHD) in children is vital for timely intervention and improved outcomes. Functional magnetic resonance imaging (fMRI) has emerged as a valuable tool for understanding the neural basis of ADHD. This abstract explores the significance of ea...

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Main Author: Nur Atiqah, Kamal
Format: Undergraduates Project Papers
Language:English
Published: 2023
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/40905/1/CB20178.pdf
http://umpir.ump.edu.my/id/eprint/40905/
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spelling my.ump.umpir.409052024-04-04T06:24:30Z http://umpir.ump.edu.my/id/eprint/40905/ Early Detection Of ADHD Among Children Using Machine Learning Nur Atiqah, Kamal QA75 Electronic computers. Computer science Early detection of attention-deficit/hyperactivity disorder (ADHD) in children is vital for timely intervention and improved outcomes. Functional magnetic resonance imaging (fMRI) has emerged as a valuable tool for understanding the neural basis of ADHD. This abstract explores the significance of early ADHD detection, the potential of fMRI for ADHD diagnosis, and the role of machine learning in facilitating early identification. By measuring brain activity patterns, fMRI provides insights into the functional abnormalities associated with ADHD. Machine learning algorithms can analyze fMRI data and identify biomarkers indicative of ADHD, enabling accurate classification. The integration of fMRI and machine learning offers a promising approach to early ADHD detection, allowing for personalized interventions and tailored treatment strategies. Early identification using fMRI and machine learning holds great potential for improving the lives of children with ADHD through timely interventions and targeted support. 2023-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40905/1/CB20178.pdf Nur Atiqah, Kamal (2023) Early Detection Of ADHD Among Children Using Machine Learning. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Nur Atiqah, Kamal
Early Detection Of ADHD Among Children Using Machine Learning
description Early detection of attention-deficit/hyperactivity disorder (ADHD) in children is vital for timely intervention and improved outcomes. Functional magnetic resonance imaging (fMRI) has emerged as a valuable tool for understanding the neural basis of ADHD. This abstract explores the significance of early ADHD detection, the potential of fMRI for ADHD diagnosis, and the role of machine learning in facilitating early identification. By measuring brain activity patterns, fMRI provides insights into the functional abnormalities associated with ADHD. Machine learning algorithms can analyze fMRI data and identify biomarkers indicative of ADHD, enabling accurate classification. The integration of fMRI and machine learning offers a promising approach to early ADHD detection, allowing for personalized interventions and tailored treatment strategies. Early identification using fMRI and machine learning holds great potential for improving the lives of children with ADHD through timely interventions and targeted support.
format Undergraduates Project Papers
author Nur Atiqah, Kamal
author_facet Nur Atiqah, Kamal
author_sort Nur Atiqah, Kamal
title Early Detection Of ADHD Among Children Using Machine Learning
title_short Early Detection Of ADHD Among Children Using Machine Learning
title_full Early Detection Of ADHD Among Children Using Machine Learning
title_fullStr Early Detection Of ADHD Among Children Using Machine Learning
title_full_unstemmed Early Detection Of ADHD Among Children Using Machine Learning
title_sort early detection of adhd among children using machine learning
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40905/1/CB20178.pdf
http://umpir.ump.edu.my/id/eprint/40905/
_version_ 1822924265481043968
score 13.235367

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