Publication Name	World Journal of Clinical Cases
Manuscript ID	87208
Country	India

Received	2023-07-29 07:09
Peer-Review Started	2023-07-29 07:11
To Make the First Decision
Return for Revision	2023-08-16 05:49
Revised	2023-09-01 15:09
Second Decision	2023-09-18 02:37
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2023-09-18 08:26
Articles in Press	2023-09-18 08:26
Publication Fee Transferred
Edit the Manuscript by Language Editor	2023-09-17 19:57
Typeset the Manuscript	2023-09-27 06:56
Publish the Manuscript Online	2023-10-13 14:28

ISSN	2307-8960 (online)
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/
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Category	Rehabilitation
Manuscript Type	Letter to the Editor
Article Title	Artificial intelligence and machine learning in motor recovery: A rehabilitation medicine perspective
Manuscript Source	Unsolicited Manuscript
All Author List	Raktim Swarnakar and Shiv Lal Yadav
ORCID	Author(s) ORCID Number Raktim Swarnakar http://orcid.org/0000-0002-7221-2825
Funding Agency and Grant Number
Corresponding Author	Raktim Swarnakar, MBBS, MD, Doctor, Department of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, Delhi, India. raktimswarnakar@hotmail.com
Key Words	Artificial intelligence; Motor learning; Rehabilitation; Motor recovery; Machine learning; Physical medicine and rehabilitation
Core Tip	Artificial intelligence (AI) and machine learning (ML) are promising to revolutionize motor recovery in rehabilitation medicine. These technologies enable precise movement analysis, personalized treatment plans, and adaptive neurorehabilitation approaches using wearable sensors, virtual reality, augmented reality, and robotic devices. AI-driven telerehabilitation also facilitates remote monitoring and consultation. However, healthcare professionals must interpret AI-generated insights and prioritize patient safety. Ongoing research will determine the true potential of AI and ML in shaping the future of rehabilitation medicine.
Publish Date	2023-10-13 14:28
Citation	Swarnakar R, Yadav SL. Artificial intelligence and machine learning in motor recovery: A rehabilitation medicine perspective. World J Clin Cases 2023; 11(29): 7258-7260
URL	https://www.wjgnet.com/2307-8960/full/v11/i29/7258.htm
DOI	https://dx.doi.org/10.12998/wjcc.v11.i29.7258

Full Article (PDF)	WJCC-11-7258-with-cover.pdf
Full Article (Word)	WJCC-11-7258.docx
Manuscript File	87208_Auto_Edited-CL-Filipodia CL-JLW.docx
Answering Reviewers	87208-Answering reviewers.pdf
Audio Core Tip	87208-Audio core tip.ogg
Conflict-of-Interest Disclosure Form	87208-Conflict-of-interest statement.pdf
Copyright License Agreement	87208-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	87208-Language certificate.pdf
Peer-review Report	87208-Peer-review(s).pdf
Scientific Misconduct Check	87208-Bing-Lin C-2.png
Scientific Editor Work List	87208-Scientific editor work list.pdf