Robotics & Machine Learning Daily News2024,Issue(Nov.20) :78-79.

Shanghai Jiao Tong University School of Medicine Reports Findings in Sepsis (Met abolic biomarkers of neonatal sepsis: identification using metabolomics combined with machine learning)

上海交通大学医学院报告脓毒症的发现(新生儿脓毒症代谢生物标志物:代谢组学与机器学习相结合的鉴定)

Robotics & Machine Learning Daily News2024,Issue(Nov.20) :78-79.

Shanghai Jiao Tong University School of Medicine Reports Findings in Sepsis (Met abolic biomarkers of neonatal sepsis: identification using metabolomics combined with machine learning)

上海交通大学医学院报告脓毒症的发现(新生儿脓毒症代谢生物标志物:代谢组学与机器学习相结合的鉴定)

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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-血液疾病和疾病的新研究-脓毒症是一篇报道的主题。根据NewsRx记者在上海的新闻报道,研究Sep SIS是与新生儿和婴儿死亡率相关的常见疾病,对于诊断,血培养是目前的金标准方法,但其阳性率低,需要更多发育2天。同时,不幸的是,ly是早期和及时诊断乳腺癌的特异性生物标志物临床实践中缺乏INFA NTS中的脓毒症和确定该疾病严重程度的方法。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Blood Diseases and Con ditions - Sepsis is the subject of a report.According to news reporting from Sh anghai, People’s Republic of China, by NewsRx journalists, researchstated, “Sep sis is a common disease associated with neonatal and infant mortality, and for d iagnosis,blood culture is currently the gold standard method, but it has a low positivity rate and requires more than2 days to develop. Meanwhile, unfortunate ly, the specific biomarkers for the early and timely diagnosis ofsepsis in infa nts and for the determination of the severity of this disease are lacking in cli nical practice.”

Key words

Shanghai/People’s Republic of China/As ia/Biomarkers/Blood Diseases and Conditions/Bloodstream Infection/Cyborgs/D iagnostics and Screening/Emerging Technologies/Health and Medicine/Machine Le arning/Sepsis/Septicemia

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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