{"title":"Artificial Intelligence and Machine Learning in Preeclampsia.","authors":"Anita T Layton","doi":"10.1161/ATVBAHA.124.321673","DOIUrl":null,"url":null,"abstract":"<p><p>Preeclampsia is a multisystem hypertensive disorder that manifests itself after 20 weeks of pregnancy, along with proteinuria. The pathophysiology of preeclampsia is incompletely understood. Artificial intelligence, especially machine learning with its capability to identify patterns in complex data, has the potential to revolutionize preeclampsia research. These data-driven techniques can improve early diagnosis, personalize risk assessment, uncover the disease's molecular basis, optimize treatments, and enable remote monitoring. This brief review discusses the recent applications of artificial intelligence and machine learning in preeclampsia management and research, including the improvements these approaches have brought, along with their challenges and limitations.</p>","PeriodicalId":8401,"journal":{"name":"Arteriosclerosis, Thrombosis, and Vascular Biology","volume":" ","pages":""},"PeriodicalIF":7.4000,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Arteriosclerosis, Thrombosis, and Vascular Biology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1161/ATVBAHA.124.321673","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEMATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Preeclampsia is a multisystem hypertensive disorder that manifests itself after 20 weeks of pregnancy, along with proteinuria. The pathophysiology of preeclampsia is incompletely understood. Artificial intelligence, especially machine learning with its capability to identify patterns in complex data, has the potential to revolutionize preeclampsia research. These data-driven techniques can improve early diagnosis, personalize risk assessment, uncover the disease's molecular basis, optimize treatments, and enable remote monitoring. This brief review discusses the recent applications of artificial intelligence and machine learning in preeclampsia management and research, including the improvements these approaches have brought, along with their challenges and limitations.
期刊介绍:
The journal "Arteriosclerosis, Thrombosis, and Vascular Biology" (ATVB) is a scientific publication that focuses on the fields of vascular biology, atherosclerosis, and thrombosis. It is a peer-reviewed journal that publishes original research articles, reviews, and other scholarly content related to these areas. The journal is published by the American Heart Association (AHA) and the American Stroke Association (ASA).
The journal was published bi-monthly until January 1992, after which it transitioned to a monthly publication schedule. The journal is aimed at a professional audience, including academic cardiologists, vascular biologists, physiologists, pharmacologists and hematologists.