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9/18/2023 8:26:37 AM | Browse: 76 | Download: 0
Publication Name World Journal of Clinical Cases
Manuscript ID 87208
Country India
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
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.
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
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
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
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/
Copyright © The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
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