Denis Satoshi Komoda, Marilia Mastrocolla de Almeida Cardoso, Brígida Dias Fernandes, Marília Berlofa Visacri, Carlos Roberto Silveira Correa
{"title":"Artificial intelligence applied in human health technology assessment: a scoping review protocol.","authors":"Denis Satoshi Komoda, Marilia Mastrocolla de Almeida Cardoso, Brígida Dias Fernandes, Marília Berlofa Visacri, Carlos Roberto Silveira Correa","doi":"10.11124/JBIES-23-00377","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Introduction: </strong>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.</p><p><strong>Inclusion criteria: </strong>This review will consider studies that assesses 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.</p><p><strong>Methods: </strong>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.</p><p><strong>Details of this review can be found in open science framework: </strong>osf.io/3rm8g.</p>","PeriodicalId":36399,"journal":{"name":"JBI evidence synthesis","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JBI evidence synthesis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11124/JBIES-23-00377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: 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 assesses 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.
Details of this review can be found in open science framework: osf.io/3rm8g.
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