Publication
Artificial intelligence in the education of health professions: a descriptive analysis through bibliometrics
| dc.contributor.author | Alves Lopes, António | |
| dc.date.accessioned | 2023-07-05T13:24:59Z | |
| dc.date.available | 2023-07-05T13:24:59Z | |
| dc.date.issued | 2023-07-03 | |
| dc.description.abstract | Introduction and Objectives: Artificial intelligence (AI) refers to a branch of computer science that focuses on creating machines and software programs that can perform tasks that typically require human-like intelligence, such as learning, problem-solving, decision making, and language understanding. AI technologies include machine learning, deep learning, natural language processing, and computer vision, among others. AI has applications in various fields, including healthcare, finance, education, among others, and has the potential to transform how we live, work, and interact with technology. AI has the potential to revolutionize the education of healthcare professionals by providing new tools and resources for teaching and training, such as personalized learning, intelligent tutoring, virtual simulation, and automated grading. The use of AI in healthcare education is growing, and it has the potential to impact research as well. However, the vast amount of scientific literature in this field makes it challenging to understand its scientific structure and development. Visualization techniques based on bibliometric data can be helpful in comprehending scientific fields. Material and Methods: This is a bibliometric, descriptive, and retrospective study. The author identified publications from the Pubmed database from 1990 till 2023 related to the use of Artificial Intelligence in Health Professions Education using this search string (AI OR "Artificial Intelligence"[Mesh]) AND "Education"[Mesh] AND "Health Personnel"[Mesh]. From the titles and abstracts of these publications, was selected the main terms related to the field, extracted by VOSviewer software, to create a visualization of the most important trends referred to in the literature. Results: The researchers identified a total of 576 relevant references, including 36 clinical trials and randomized controlled trials, as well as 57 meta-analyses and systematic reviews. Upon examining the co-occurrence of Mesh terms associated with AI and healthcare professionals' education, it was found that the most common usage of this approach was in various medical fields and educational levels, followed by allied health personnel. Another noteworthy observation was the emergence of the use of AI in healthcare education in surgery, which began to gain traction after 2018. Conclusions: Overall, as shown by published research, the interest in AI has grown exponentially, influencing all aspects related to the use of this approach in the education and training of healthcare professions. The use of AI in healthcare education has the potential to enhance the learning experience for students, improve their clinical skills and decision-making abilities, and ultimately lead to better patient outcomes. However, it is important to ensure that these technologies are designed and implemented in an ethical and responsible manner, with appropriate consideration given to issues such as bias, privacy, and transparency. | pt_PT |
| dc.description.version | N/A | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.26/45401 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Artificial intelligence | pt_PT |
| dc.subject | Health professions | pt_PT |
| dc.subject | Bibliometrics | pt_PT |
| dc.title | Artificial intelligence in the education of health professions: a descriptive analysis through bibliometrics | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Palma, Espanha | pt_PT |
| oaire.citation.title | EDULEARN23 - 15th annual International Conference on Education and New Learning Technologies | pt_PT |
| person.familyName | Alves Lopes | |
| person.givenName | António | |
| person.identifier.ciencia-id | 0518-F2A3-C5B4 | |
| person.identifier.orcid | 0000-0001-7505-6744 | |
| person.identifier.scopus-author-id | 57217386138 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 3680dab5-8822-4558-918a-df699bda57ad | |
| relation.isAuthorOfPublication.latestForDiscovery | 3680dab5-8822-4558-918a-df699bda57ad |
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