Artificial Intelligence and Machine Learning in Preeclampsia.

IF 7.4 1区 医学 Q1 HEMATOLOGY
Anita T Layton
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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.

人工智能和机器学习在先兆子痫中的应用。
子痫前期是一种多系统高血压疾病,在妊娠20周后出现,并伴有蛋白尿。子痫前期的病理生理尚不完全清楚。人工智能,特别是具有识别复杂数据模式能力的机器学习,有可能彻底改变子痫前期研究。这些数据驱动的技术可以改善早期诊断,个性化风险评估,揭示疾病的分子基础,优化治疗,并实现远程监测。本文简要讨论了人工智能和机器学习在子痫前期管理和研究中的最新应用,包括这些方法带来的改进,以及它们的挑战和局限性。
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来源期刊
CiteScore
15.60
自引率
2.30%
发文量
337
审稿时长
2-4 weeks
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.
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