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0035/2026 - ARTIFICIAL INTELLIGENCE AND KNOWLEDGE TRANSLATION IN HEALTHCARE: A SCOPE REVIEW
INTELIGÊNCIA ARTIFICIAL E TRADUÇÃO DO CONHECIMENTO EM SAÚDE: UMA REVISÃO DE ESCOPO

Author:

• Herbert Nunes Batista Glória - Glória, HNB - <hebertnunes42@gmail.com>
ORCID: https://orcid.org/0009-0006-5890-4186

Co-author(s):

• Thaís Branquinho Oliveira Fragelli - Fragelli, TBO - <thaisfragelli@unb.br>
ORCID: https://orcid.org/0000-0001-9378-0066


Abstract:

The use of artificial intelligence has been increasing in various fields, including healthcare. The objective of this study was to investigate how artificial intelligence is used for knowledge translation in healthcare. A scoping review was conducted using Embase, Medline via PubMed, Scopus, and Web of Science databases, as well as terms from the Health Sciences Descriptors (DeCS), Medical Subject Headings (MeSH), and Emtree (Embase). The types of knowledge translation identified were mostly post-project translation, followed by integrated translation. The most frequently targeted audience was healthcare professionals, with primary care being the most addressed, emphasizing health education. The most frequently cited types of artificial intelligence were Machine Learning, followed by Large Language Models and Natural Language Processing. The conclusion is that artificial intelligence remains a developing field; studies are still exploratory and require further in-depth research but may expand as knowledge and development in the field progress.

Keywords:

artificial intelligence, knowledge translation, public health, digital health.

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