Artificial intelligence and knowledge translation in healthcare: a scoping review

The use of artificial intelligence has been increasing in various fields, including healthcare. The present study aimed 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 Health Care (PHC) being the most widely 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 continues to be a developing field. The studies are still exploratory, require further investigation, and may expand as a result of greater knowledge and development in the field.