Artificial intelligence applied in human health technology assessment: a scoping review protocol

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual de Campinas (UNICAMP)-
Autor(es): dc.contributorA JBI Centre of Excellence-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorPesquisa e Inovação em Saúde (ICEPi)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorKomoda, Denis Satoshi-
Autor(es): dc.creatorde Almeida Cardoso, Marilia Mastrocolla-
Autor(es): dc.creatorFernandes, Brígida Dias-
Autor(es): dc.creatorVisacri, Marília Berlofa-
Autor(es): dc.creatorCorrea, Carlos Roberto Silveira-
Data de aceite: dc.date.accessioned2025-08-21T20:19:01Z-
Data de disponibilização: dc.date.available2025-08-21T20:19:01Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-09-03-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.11124/JBIES-23-00377-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/297770-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/297770-
Descrição: dc.descriptionObjective: This scoping review aims to map studies that applied artificial intelligence (AI) tools to perform health technology assessment tasks in human health care. The review also aims to understand specific processes in which the AI tools were applied and to comprehend the technical characteristics of these tools. Introduction: Health technology assessment is a complex, time-consuming, and labor-intensive endeavor. The development of automation techniques using AI has opened up new avenues for accelerating such assessments in human health settings. This could potentially aid health technology assessment researchers and decision-makers to deliver higher quality evidence. Inclusion criteria: This review will consider studies that assess the use of AI tools in any process of health technology assessment in human health. However, publications in which AI is a means of clinical aid, such as diagnostics or surgery will be excluded. Methods: A search for relevant articles will be conducted in databases such as CINAHL (EBSCOhost), Embase (Ovid), MEDLINE (PubMed), Science Direct, Computer and Applied Sciences Complete (EBSCOhost), LILACS, Scopus, and Web of Science Core Collection. A search for gray literature will be conducted in GreyLit.Org, ProQuest Dissertations and Theses, Google Scholar, and the Google search engine. No language filters will be applied. Screening, selection, and data extraction will be performed by 2 independent reviewers. The results will be presented in graphic and tabular format, accompanied by a narrative summary.-
Descrição: dc.descriptionDepartment of Collective Health Faculty of Medical Sciences University of Campinas, SP-
Descrição: dc.descriptionBrazilian Centre for Evidence-based Healthcare A JBI Centre of Excellence, SP-
Descrição: dc.descriptionHealth Technology Assessment Center Hospital das Clinicas of Medical School (FMB) São Paulo State University (Unesp), SP-
Descrição: dc.descriptionInstituto Capixaba de Ensino Pesquisa e Inovação em Saúde (ICEPi), ES-
Descrição: dc.descriptionDepartment of Pharmacy Faculty of Pharmaceutical Sciences University of São Paulo, SP-
Descrição: dc.descriptionHealth Technology Assessment Center Hospital das Clinicas of Medical School (FMB) São Paulo State University (Unesp), SP-
Formato: dc.format2559-2566-
Idioma: dc.languageen-
Relação: dc.relationJBI Evidence Synthesis-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectartificial intelligence-
Palavras-chave: dc.subjectautomation-
Palavras-chave: dc.subjecthealth technology assessment-
Palavras-chave: dc.subjectmachine learning-
Palavras-chave: dc.subjectscoping review-
Título: dc.titleArtificial intelligence applied in human health technology assessment: a scoping review protocol-
Tipo de arquivo: dc.typevídeo-
Aparece nas coleções:Repositório Institucional - Unesp

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