The Impact of Generative Artificial Intelligence on the Development, Evaluation, and Application of Clinical Practice Guidelines

Generative artificial intelligence (GAI) refers to AI technology capable of generating new content such as text, images, or audio from training data. GAI tools not only demonstrate rapid and efficient potential in literature screening, data extraction, and literature appraisal in systematic reviews, but can also be used for guideline evaluation and dissemination, enhancing the readability and promotion efficiency of guidelines. However, the accuracy of content generated by GAI tools, the rationality of cited evidence, the level of evidence, and the reliability of data still need verification. Additionally, data privacy protection and ethical issues are challenges that need to be addressed. This article aims to overview the current status of GAI tools in the formulation, evaluation, dissemination, and implementation of guidelines, explore the feasibility and new models of GAI tools in the field of guidelines, and improve the efficiency and quality of guideline formulation to better serve guideline developers and users.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.12290/xhyxzz.2024-0602
Citations
1
Primary Topic
Mycorrhizal Fungi and Plant Interactions
Type
article
Field-Weighted Citation Impact
0.60
Controls
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article

The Impact of Generative Artificial Intelligence on the Development, Evaluation, and Application of Clinical Practice Guidelines

1 citations
SHILAP Revista de lepidopterología
Mycorrhizal Fungi and Plant Interactions
0.60
article

The Impact of Generative Artificial Intelligence on the Development, Evaluation, and Application of Clinical Practice Guidelines

article en
1 citations

Abstract

Generative artificial intelligence (GAI) refers to AI technology capable of generating new content such as text, images, or audio from training data. GAI tools not only demonstrate rapid and efficient potential in literature screening, data extraction, and literature appraisal in systematic reviews, but can also be used for guideline evaluation and dissemination, enhancing the readability and promotion efficiency of guidelines. However, the accuracy of content generated by GAI tools, the rationality of cited evidence, the level of evidence, and the reliability of data still need verification. Additionally, data privacy protection and ethical issues are challenges that need to be addressed. This article aims to overview the current status of GAI tools in the formulation, evaluation, dissemination, and implementation of guidelines, explore the feasibility and new models of GAI tools in the field of guidelines, and improve the efficiency and quality of guideline formulation to better serve guideline developers and users.

SHILAP Revista de lepidopterología
Hong Kong Baptist University (HK), Capital Medical University (CN), Peking University (CN), Peking University Third Hospital (CN), Beijing Friendship Hospital (CN), Lanzhou University (CN), Southwest Baptist University (US)
Quality Education
Openalex Percentile: Top 19%
Mycorrhizal Fungi and Plant Interactions
0.60
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The Impact of Generative Artificial Intelligence on the Development, Evaluation, and Application of Clinical Practice Guidelines · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS