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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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/40905/ http://umpir.ump.edu.my/id/eprint/40905/1/CB20178.pdf |
| _version_ | 1848826180798513152 |
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| author | Nur Atiqah, Kamal |
| author_facet | Nur Atiqah, Kamal |
| author_sort | Nur Atiqah, Kamal |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T03:40:44Z |
| format | Undergraduates Project Papers |
| id | ump-40905 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:40:44Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-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. |
| spellingShingle | QA75 Electronic computers. Computer science Nur Atiqah, Kamal Early Detection Of ADHD Among Children Using Machine Learning |
| title | 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_short | Early Detection Of ADHD Among Children Using Machine Learning |
| title_sort | early detection of adhd among children using machine learning |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/40905/ http://umpir.ump.edu.my/id/eprint/40905/1/CB20178.pdf |