[Artificial intelligence for the comprehensive approach to orphan/rare diseases: A scoping review].

IF 0.9 Q4 PRIMARY HEALTH CARE
L M Acero Ruge, D A Vásquez Lesmes, E H Hernández Rincón, L P Avella Pérez
{"title":"[Artificial intelligence for the comprehensive approach to orphan/rare diseases: A scoping review].","authors":"L M Acero Ruge, D A Vásquez Lesmes, E H Hernández Rincón, L P Avella Pérez","doi":"10.1016/j.semerg.2024.102434","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Orphan diseases (OD) are rare but collectively common, presenting challenges such as late diagnoses, disease progression, and limited therapeutic options. Recently, artificial intelligence (AI) has gained interest in the research of these diseases.</p><p><strong>Objective: </strong>To synthesize the available evidence on the use of AI in the comprehensive approach to orphan diseases.</p><p><strong>Methods: </strong>An exploratory systematic review of the Scoping Review type was conducted in PubMed, Bireme, and Scopus from 2019 to 2024.</p><p><strong>Results: </strong>fifty-six articles were identified, with 21.4% being experimental studies; 28 documents did not specify an OD, 8 documents focused primarily on genetic diseases; 53.57% focused on diagnosis, and 36 different algorithms were identified.</p><p><strong>Conclusions: </strong>The information found shows the development of AI algorithms in different clinical settings, confirming the potential benefits in diagnosis times, therapeutic options, and greater awareness among health professionals.</p>","PeriodicalId":53212,"journal":{"name":"Medicina de Familia-SEMERGEN","volume":"51 5","pages":"102434"},"PeriodicalIF":0.9000,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medicina de Familia-SEMERGEN","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.semerg.2024.102434","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PRIMARY HEALTH CARE","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Orphan diseases (OD) are rare but collectively common, presenting challenges such as late diagnoses, disease progression, and limited therapeutic options. Recently, artificial intelligence (AI) has gained interest in the research of these diseases.

Objective: To synthesize the available evidence on the use of AI in the comprehensive approach to orphan diseases.

Methods: An exploratory systematic review of the Scoping Review type was conducted in PubMed, Bireme, and Scopus from 2019 to 2024.

Results: fifty-six articles were identified, with 21.4% being experimental studies; 28 documents did not specify an OD, 8 documents focused primarily on genetic diseases; 53.57% focused on diagnosis, and 36 different algorithms were identified.

Conclusions: The information found shows the development of AI algorithms in different clinical settings, confirming the potential benefits in diagnosis times, therapeutic options, and greater awareness among health professionals.

[人工智能用于孤儿/罕见病的综合方法:范围审查]。
孤儿病(Orphan disease, OD)是一种罕见但普遍的疾病,存在诊断晚、疾病进展和治疗选择有限等挑战。近年来,人工智能(AI)对这些疾病的研究产生了兴趣。目的:综合人工智能在孤儿病综合治疗中的应用。方法:对2019 - 2024年PubMed、Bireme和Scopus进行Scoping review类型的探索性系统评价。结果:共纳入56篇文献,其中实验研究占21.4%;28份文件没有指定OD, 8份文件主要侧重于遗传病;53.57%的人关注于诊断,共有36种不同的算法。结论:发现的信息显示了人工智能算法在不同临床环境中的发展,证实了在诊断时间、治疗选择和卫生专业人员意识提高方面的潜在益处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Medicina de Familia-SEMERGEN
Medicina de Familia-SEMERGEN PRIMARY HEALTH CARE-
CiteScore
1.40
自引率
18.20%
发文量
83
审稿时长
39 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信