Suppr超能文献

人工智能与机器学习在子痫前期中的应用

Artificial Intelligence and Machine Learning in Preeclampsia.

作者信息

Layton Anita T

机构信息

Department of Applied Mathematics, Department of Biology, Cheriton School of Computer Science, and School of Pharmacology, University of Waterloo, ON, Canada.

出版信息

Arterioscler Thromb Vasc Biol. 2025 Feb;45(2):165-171. doi: 10.1161/ATVBAHA.124.321673. Epub 2025 Jan 2.

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.

摘要

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学尚未完全了解。人工智能,尤其是具有在复杂数据中识别模式能力的机器学习,有可能彻底改变子痫前期的研究。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。本简要综述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面临的挑战和局限性。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验