Researchers at University of Leuven (KU Leuven) Target Machine Learning (Compari son between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate)

鲁汶大学(KU Leuven)的研究人员瞄准机器学习(EKFC方程和机器学习模型预测肾小球滤过率的比较)

Robotics & Machine Learning Daily News2024，Issue(Nov.20) ：33-34.

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Researchers at University of Leuven (KU Leuven) Target Machine Learning (Compari son between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate)

鲁汶大学(KU Leuven)的研究人员瞄准机器学习(EKFC方程和机器学习模型预测肾小球滤过率的比较)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于人工智能的详细数据已经呈现。根据新闻报道由NewsRx通讯员从鲁汶大学（KU Leuven）发起的研究表明，“在临床实践中，肾小球滤过率(GFR)，一种肾功能的测量值，正常情况下，肾小球滤过率低于正常水平。”使用公式计算，如欧洲肾功能离子联盟(EKFC)公式。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on artificial intelligen ce have been presented. According to news reportingoriginating from the Univers ity of Leuven (KU Leuven) by NewsRx correspondents, research stated, “In clinica l practice, the glomerular filtration rate (GFR), a measurement of kidney functi oning, is normallycalculated using equations, such as the European Kidney Funct ion Consortium (EKFC) equation.”

Key words

University of Leuven (KU Leuven)/Cyborg s/Emerging Technologies/Machine Learning

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出版年

2024

Robotics & Machine Learning Daily News

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