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TECHNOLOGY AND CODE article

Front. Public Health
Sec. Digital Public Health
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1364660
This article is part of the Research Topic Ethical Considerations in Electronic Data in Healthcare View all 7 articles

Large Language Models in Physical therapy: time to adapt and adept

Provisionally accepted
Waqar M. Naqvi Waqar M. Naqvi 1,2Summaiya Zareen Shaikh Summaiya Zareen Shaikh 3*Gaurav Mishra Gaurav Mishra 2
  • 1 Gulf Medical University, Ajman, Ajman, United Arab Emirates
  • 2 Datta Meghe Institute of Higher Education and Research, Wardha, Maharashtra, India
  • 3 The South Indian Association College of Health Sciences College of Physiotherapy, Thane, India

The final, formatted version of the article will be published soon.

    Healthcare is experiencing a transformative phase, with Artificial Intelligence (AI) and Machine Learning (ML). Physical therapists (PT) stand on the brink of a paradigm shift in education, practice, and research. Rather than visualizing AI as a threat, it presents an opportunity to revolutionize. This paper examines how Large Language Models (LLMs), such as ChatGPT and BioMedLM, driven by deep machine learning can offer human-like performance but face challenges in accuracy due to vast data in PT and rehabilitation practice.PTs can benefit by developing and training an LLM specifically into streamlining administrative tasks, connecting globally, customizing treatments using LLMs. However, human touch and creativity remains invaluable. This paper urges physical therapists to engage in learning and shaping AI models by highlighting the need for ethical use and human supervision to address potential biases. Embracing AI as a contributor, and not just a user, is crucial by integrating AI, fostering collaboration for a future in which AI enriches the PT field provided data accuracy, and the challenges associated with feeding the AI model are sensitively addressed.

    Keywords: artificial intelligence, Biomed LM, evidence based practice, Large language models, Physical Therapy, Physical therapy education, Rehabilitation

    Received: 02 Jan 2024; Accepted: 10 May 2024.

    Copyright: © 2024 Naqvi, Shaikh and Mishra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Summaiya Zareen Shaikh, The South Indian Association College of Health Sciences College of Physiotherapy, Thane, India

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.