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Review Article

Artificial Intelligence in Decoding ADHD (Attention Deficit Hyperactivity Disorder)

Prachi Srivastava, Amaan Arif, Shrijal Singh

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Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

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International Journal of Neurology and Neurosurgery 16(1-2):p 7-16, January-June 2024. | DOI: https://doi.org/10.21088/ijnns.0975.0223.161224.1

How Cite This Article:

Prachi Srivastava, Amaan Arif, Shrijal Singh. Artificial Intelligence in Decoding ADHD (Attention Deficit Hyperactivity Disorder). International Journal of Neurology and Neurosurgery. 2024;16(1-2):07-16.

Timeline

Received : January 07, 2024         Accepted : May 29, 2024          Published : June 30, 2024

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder that affects both children and adults, is characterized by symptoms of inattention, hyperactivity, and impulsivity. Globally, ADHD affects approximately 5-7% of children and adolescents, as well as 2.5% of adults. The condition significantly impacts daily functioning, social relationships or interactions, and academic or professional performance. ADHD appears differently in different age groups, with classroom disruptions and difficulty in social interactions being common in children, while adults may struggle with time management, organizing, and maintaining interpersonal connections. The disorder is categorized into three main types: mainly inattentive, mostly hyperactive-impulsive, and combination presentation, which are defined by dominant symptom patterns. Diagnosis involves ongoing symptom assessment, with treatment options including medications, behavioural therapies, and management strategies tailored to individual needs. The growing use of Artificial Intelligence (AI) in healthcare has significantly improved ADHD diagnosis and treatment, offering higher precision, efficiency, and personalization. AI algorithms enhance diagnostic accuracy by analyzing large datasets and identifying complex patterns in medical images, enabling early detection of ADHD and related conditions. Moreover, AI-driven treatment plans personalize therapeutic techniques based on individual patient data, improving outcomes and reducing adverse side effects. Benefits of AI include improved diagnostic accuracy, increased efficiency through automation, development of personalized medicine, and reduced healthcare costs. This review explores the role of AI in ADHD diagnosis and treatment, focusing on its transformative potential in improving patient care and advancing precision medicine. Understanding AI applications in healthcare can lead to way for more effective ADHD therapy management and improved patient quality of life.


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Data Sharing Statement

There are no additional data available. All raw data and code are available upon request.

Funding

This research received no funding.

Author Contributions

All authors contributed significantly to the work and approve its publication.

Ethics Declaration

This article does not involve any human or animal subjects, and therefore does not require ethics approval.

Acknowledgements

We would like to express our gratitude to the patients, their families, and all those who have contributed to this study.

Conflicts of Interest

No conflicts of interest in this work.


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Cite this article

Prachi Srivastava, Amaan Arif, Shrijal Singh. Artificial Intelligence in Decoding ADHD (Attention Deficit Hyperactivity Disorder). International Journal of Neurology and Neurosurgery. 2024;16(1-2):07-16.


Licence:

Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.


Received Accepted Published
January 07, 2024 May 29, 2024 June 30, 2024

DOI: https://doi.org/10.21088/ijnns.0975.0223.161224.1

Keywords

ADHDNeurodevelopmental disorderInattentionHyperactivityImpulsivityDiagnosistreatmentChildrenAdults

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Received January 07, 2024
Accepted May 29, 2024
Published June 30, 2024

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Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)

This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.


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