Robotics & Machine Learning Daily News2024,Issue(Jun.4) :73-74.

Shenzhen Maternity & Child Healthcare Hospital Reports Findings in Machine Learning (Lipidomics random forest algorithm of seminal plasma is a pro mising method for enhancing the diagnosis of necrozoospermia)

深圳市妇幼保健院报告机器学习发现(精浆脂质组学随机森林算法是提高尸检诊断水平的有效方法)

Robotics & Machine Learning Daily News2024,Issue(Jun.4) :73-74.

Shenzhen Maternity & Child Healthcare Hospital Reports Findings in Machine Learning (Lipidomics random forest algorithm of seminal plasma is a pro mising method for enhancing the diagnosis of necrozoospermia)

深圳市妇幼保健院报告机器学习发现(精浆脂质组学随机森林算法是提高尸检诊断水平的有效方法)

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摘要

一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。根据《中华人民共和国深圳消息》,NewsRx记者报道,研究表明:“尽管男科坏死精子症的临床诊断标准很明确,但其发生的基本机制和机理尚不清楚,本研究旨在系统地分析女性血浆中的脂质成分,并确定脂质生物标志物在准确诊断坏死精子症中的潜力。”本研究的资助者包括深圳市科技创新委员会、深圳市重点医学学科建设基金、深港马科技计划。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news originating from Shenzhen, People’s Republic of Ch ina, by NewsRx correspondents, research stated, “Despite the clear clinical diag nostic criteria for necrozoospermia in andrology, the fundamental mechanisms und erlying it remain elusive. This study aims to profile the lipid composition in s eminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia.” Funders for this research include Shenzhen Science and Technology Innovation Com mittee, Shenzhen Key Medical Discipline Construction Fund, Shenzhen-Hong Kong-Ma cau Science and Technology Program.

Key words

Shenzhen/People’s Republic of China/As ia/Algorithms/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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