Use of artificial intelligence in neurological disorders diagnosis: A scientometric study

doi:10.5662/wjm.v15.i3.99403

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World Journal of Methodology

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2222-0682

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Scientometrics

World J Methodol. Sep 20, 2025; 15(3): 99403
Published online Sep 20, 2025. doi: 10.5662/wjm.v15.i3.99403

Use of artificial intelligence in neurological disorders diagnosis: A scientometric study

Alaa Tarazi, Ahmad Aburrub, Mohammad Hijah

Alaa Tarazi, Ahmad Aburrub, Mohammad Hijah, School of Medicine, University of Jordan, Amman 11942, Jordan

Author contributions: Tarazi A had the idea of the article and its design, collected the data, contributed to the study conception and its design, conducted the data analysis, investigation, writing original draft, editing, and review; Aburrub A contributed to the study conception and design, did the data curation, investigation, writing of original draft, editing, and review; Hijah M contributed to the study conception and design, did the data curation, investigation, writing of original draft, editing, and review.

Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.

PRISMA 2009 Checklist statement: The PRISMA checklist file was provided in the first submission and will be provided again this time.

Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/

Corresponding author: Alaa Tarazi, MD, Doctor, School of Medicine, University of Jordan, Queen Rania St, Amman 11942, Jordan. alaatarazi11@gmail.com

Received: July 21, 2024
Revised: December 3, 2024
Accepted: December 23, 2024
Published online: September 20, 2025
Processing time: 227 Days and 2.6 Hours

Abstract

BACKGROUND

Artificial intelligence (AI) has become significantly integrated into healthcare, particularly in the diagnosing of neurological disorders. This advancement has enabled neurologists and physicians to diagnose conditions more quickly and effectively, ultimately benefiting patients.

AIM

To explore the current status and key highlights of AI-related articles in diagnosing of neurological disorders.

METHODS

A systematic literature review was conducted in the Web of Science Core Collection database using the following strategy: TS = ("Artificial Intelligence" OR "Computational Intelligence" OR "Machine Learning" OR "AI") AND TS = ("Neurological disorders" OR "CNS disorder" AND "diagnosis"). The search was limited to articles and reviews. Microsoft Excel 2019 and VOSviewer were utilized to identify major contributors, including authors, institutions, countries, and journals. Additionally, VOSviewer was employed to analyze and visualize current trends and hot topics through network visualization maps.

RESULTS

A total of 276 publications from 2000 to 2024 were retrieved. The United States, India, and China emerged as the top contributors in this field. Major institutions included Johns Hopkins University, King's College London, and Harvard Medical School. The most prolific author was U. Rajendra Acharya from the University of Southern Queensland (Australia). Among journals, IEEE Access, Scientific Reports, and Sensors were the most productive, while Frontiers in Neuroscience led in total citations. Central topics in AI-related articles on neurological disorders diagnosis included Alzheimer's disease, Parkinson's disease, dementia, epilepsy, autism, attention deficit hyperactivity disorder, and their intersections with deep learning and AI.

CONCLUSION

Research on AI's role in diagnosing neurological disorders is becoming widely recognized for its growing importance. AI shows promise in diagnosing various neurological disorders, yet requires further improvement and extensive future research.

Keywords: Artificial intelligence; Machine learning; Neurological disorders; Diagnosis; Bibliometric analysis

Core Tip: Artificial intelligence's (AI) role in diagnosing neurological disorders has been increasingly recognized. We conducted a scientometric analysis to explore the current status of articles in this field and identify the most prolific contributors from various perspectives. Johns Hopkins University in the United States emerged as the leading institution, with the United States also leading overall productivity in this field. IEEE Access was noted as the top journal. Research highlights AI's effectiveness in diagnosing diverse neurological disorders, offering significant benefits for patients and healthcare providers. Continued advancements are expected in AI's role in neurological disorder diagnosis.