Full Text (PDF)
Review Article

Artificial Intelligence in Decoding ADHD (Attention Deficit Hyperactivity Disorder)

Prachi Srivastava, , Prachi Srivastava1 , Amaan Arif2 , Shrijal Singh3

Author Information

Licence:




International Journal of Neurology and Neurosurgery 16(1-2):p 7-16, January-June 2024. | DOI: http://dx.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 : N/A         Accepted : N/A          Published : N/A

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.
 


References

No records found.


About this article


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:




Received Accepted Published
N/A N/A N/A

DOI: http://dx.doi.org/10.21088/ijnns.0975.0223.161224.1

Keywords

ADHD; Neurodevelopmental disorder; Inattention; Hyperactivity; Impulsivity; Diagnosis; treatment; Children; Adults

Article Level Metrics

Last Updated

Wednesday 17 June 2026, 20:31:28 (IST)


977

Accesses

3
226
00

Citations


NA
NA
NA

Download citation


Article Keywords


Keyword Highlighting

Highlight selected keywords in the article text.


Timeline


Received N/A
Accepted N/A
Published N/A

licence



Access this article



Share