The use of artificial intelligence to identify ophthalmic biomarkers in cardiovascular disease and stroke: a narrative review.

IF 1.3 4区医学 Q2 MEDICINE, GENERAL & INTERNAL

Sao Paulo Medical Journal Pub Date : 2025-05-26 eCollection Date: 2025-01-01 DOI:10.1590/1516-3180.2023.0369.11022025

Diogo Gonçalves Dos Santos Martins, Thiago Goncalves Dos Santos Martins, Paulo Schor

{"title":"The use of artificial intelligence to identify ophthalmic biomarkers in cardiovascular disease and stroke: a narrative review.","authors":"Diogo Gonçalves Dos Santos Martins, Thiago Goncalves Dos Santos Martins, Paulo Schor","doi":"10.1590/1516-3180.2023.0369.11022025","DOIUrl":null,"url":null,"abstract":"Background: Cardiovascular disease (CVD) and stroke are among the leading causes of death worldwide.Objective: This article presents a review of the application of artificial intelligence in identifying biomarkers for CVD and stroke.Design and setting: Narrative review conducted by a research group at the Universidade Federal de São Paulo, São Paulo, Brazil.Methods: A literature search was conducted to identify the main applications of artificial intelligence in ophthalmology, using the keywords \"artificial intelligence,\" \"prediction,\" \"biomarker,\" \"cardiovascular disease,\" \"retina,\" and \"stroke,\" covering the period from January 1, 2018, to July 3, 2023. The Medical Literature Analysis and Retrieval System Online (MEDLINE, via PubMed) and the Latin American and Caribbean Literature in Health Sciences (Literatura Latino-Americana e do Caribe em Ciências da Saúde, LILACS, via the Virtual Health Library) were used to identify relevant articles.Results: A total of 30 references were retrieved, of which 14 were considered eligible for intensive review and critical analysis.Conclusions: Artificial intelligence has proven effective in identifying non-invasive biomarkers through the analysis of patients' retinal examinations. These findings contribute to a better understanding of the pathophysiology of CVD and stroke.","PeriodicalId":49574,"journal":{"name":"Sao Paulo Medical Journal","volume":"143 3","pages":"e2023369"},"PeriodicalIF":1.3000,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105858/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sao Paulo Medical Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1590/1516-3180.2023.0369.11022025","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}

引用次数: 0

Abstract

Background: Cardiovascular disease (CVD) and stroke are among the leading causes of death worldwide.

Objective: This article presents a review of the application of artificial intelligence in identifying biomarkers for CVD and stroke.

Design and setting: Narrative review conducted by a research group at the Universidade Federal de São Paulo, São Paulo, Brazil.

Methods: A literature search was conducted to identify the main applications of artificial intelligence in ophthalmology, using the keywords "artificial intelligence," "prediction," "biomarker," "cardiovascular disease," "retina," and "stroke," covering the period from January 1, 2018, to July 3, 2023. The Medical Literature Analysis and Retrieval System Online (MEDLINE, via PubMed) and the Latin American and Caribbean Literature in Health Sciences (Literatura Latino-Americana e do Caribe em Ciências da Saúde, LILACS, via the Virtual Health Library) were used to identify relevant articles.

Results: A total of 30 references were retrieved, of which 14 were considered eligible for intensive review and critical analysis.

Conclusions: Artificial intelligence has proven effective in identifying non-invasive biomarkers through the analysis of patients' retinal examinations. These findings contribute to a better understanding of the pathophysiology of CVD and stroke.

查看原文本刊更多论文

使用人工智能识别心血管疾病和中风中的眼科生物标志物：叙述性回顾。

背景：心血管疾病（CVD）和中风是世界范围内导致死亡的主要原因。目的：综述人工智能在心血管疾病和脑卒中生物标志物识别中的应用。设计和设置：由巴西圣保罗联邦大学的一个研究小组进行的叙述性审查。方法：检索2018年1月1日至2023年7月3日期间人工智能在眼科的主要应用，检索关键词为“人工智能”、“预测”、“生物标志物”、“心血管疾病”、“视网膜”和“中风”。使用在线医学文献分析和检索系统（MEDLINE，通过PubMed）和拉丁美洲和加勒比健康科学文献（Literatura Latin - americana e do Caribe em Ciências da Saúde， LILACS，通过虚拟健康图书馆）来识别相关文章。结果：共检索到30篇文献，其中14篇被认为有资格进行深入审查和批判性分析。结论：通过分析患者视网膜检查，人工智能已被证明在识别非侵入性生物标志物方面是有效的。这些发现有助于更好地理解心血管疾病和中风的病理生理学。

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

Sao Paulo Medical Journal 医学-医学：内科

CiteScore

2.20

自引率

7.10%

发文量

210

审稿时长

6-12 weeks

期刊介绍： Published bimonthly by the Associação Paulista de Medicina, the journal accepts articles in the fields of clinical health science (internal medicine, gynecology and obstetrics, mental health, surgery, pediatrics and public health). Articles will be accepted in the form of original articles (clinical trials, cohort, case-control, prevalence, incidence, accuracy and cost-effectiveness studies and systematic reviews with or without meta-analysis), narrative reviews of the literature, case reports, short communications and letters to the editor. Papers with a commercial objective will not be accepted.