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Large language models in physical therapy: time to adapt and adept.
Naqvi, Waqar M; Shaikh, Summaiya Zareen; Mishra, Gaurav V.
Afiliação
  • Naqvi WM; Department of Interdisciplinary Sciences, Datta Meghe Institute of Higher Education and Research, Wardha, India.
  • Shaikh SZ; Department of Physiotherapy, College of Health Sciences, Gulf Medical University, Ajman, United Arab Emirates.
  • Mishra GV; NKP Salve Institute of Medical Sciences and Research Center, Nagpur, India.
Front Public Health ; 12: 1364660, 2024.
Article em En | MEDLINE | ID: mdl-38887241
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article