Large language models in physical therapy
Time to adapt and adept
Bibliographic Data
| ID | 22067769 |
|---|---|
| Authors | Waqar M Naqvi (0000-0003-4484-8225, Gulf Medical University), Summaiya Zareen Shaikh (corresponding author), Gaurav Mishra (0000-0003-4957-7479, Datta Meghe Institute of Medical Sciences), Gaurav V Mishra |
| Year | 2024 |
| Volume | 12 |
| Pages | 1364660-1364660 |
| Publication date | 2024-05-24 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2024.1364660 |
| PMID | 38887241 |
| OpenAlex | W4398780874 |
| Language | EN |
| Citations received | 1 |
| References cited | 53 |
Healthcare is experiencing a transformative phase, with artificial intelligence (AI) and machine learning (ML). Physical therapists (PTs) 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 ML 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 for streamlining administrative tasks, connecting globally, and customizing treatments using LLMs. However, human touch and creativity remain invaluable. This paper urges PTs 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
Creativity · Data science · Engineering ethics · Health care · Pedagogy · Political science · Transformative learning · Artificial Intelligence in Healthcare and Education · Computer Science · COVID-19 diagnosis using AI · Engineering · Psychology · Artificial Intelligence
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |