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Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery

Natural language computer applications are becoming increasingly sophisticated and, with the recent release of Generative Pre-trained Transformer 3, they could be deployed in healthcare-related contexts that have historically comprised human-to-human interaction. However, for GPT-3 and similar appli...

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Autores principales: Korngiebel, Diane M., Mooney, Sean D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175735/
https://www.ncbi.nlm.nih.gov/pubmed/34083689
http://dx.doi.org/10.1038/s41746-021-00464-x
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author Korngiebel, Diane M.
Mooney, Sean D.
author_facet Korngiebel, Diane M.
Mooney, Sean D.
author_sort Korngiebel, Diane M.
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description Natural language computer applications are becoming increasingly sophisticated and, with the recent release of Generative Pre-trained Transformer 3, they could be deployed in healthcare-related contexts that have historically comprised human-to-human interaction. However, for GPT-3 and similar applications to be considered for use in health-related contexts, possibilities and pitfalls need thoughtful exploration. In this article, we briefly introduce some opportunities and cautions that would accompany advanced Natural Language Processing applications deployed in eHealth.
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spelling pubmed-81757352021-06-07 Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery Korngiebel, Diane M. Mooney, Sean D. NPJ Digit Med Comment Natural language computer applications are becoming increasingly sophisticated and, with the recent release of Generative Pre-trained Transformer 3, they could be deployed in healthcare-related contexts that have historically comprised human-to-human interaction. However, for GPT-3 and similar applications to be considered for use in health-related contexts, possibilities and pitfalls need thoughtful exploration. In this article, we briefly introduce some opportunities and cautions that would accompany advanced Natural Language Processing applications deployed in eHealth. Nature Publishing Group UK 2021-06-03 /pmc/articles/PMC8175735/ /pubmed/34083689 http://dx.doi.org/10.1038/s41746-021-00464-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Comment
Korngiebel, Diane M.
Mooney, Sean D.
Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery
title Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery
title_full Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery
title_fullStr Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery
title_full_unstemmed Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery
title_short Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery
title_sort considering the possibilities and pitfalls of generative pre-trained transformer 3 (gpt-3) in healthcare delivery
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175735/
https://www.ncbi.nlm.nih.gov/pubmed/34083689
http://dx.doi.org/10.1038/s41746-021-00464-x
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