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A Novel Human Epithelial Enteroid Model of Necrotizing Enterocolitis

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Published on: April 10, 2019

从历史和人工智能角度了解死性肠球炎内型和获得性肠损伤表型

Alain Cuna^1,2, Navin Kumar³, Venkatesh Sampath^1,2

¹Division of Neonatology, Children's Mercy Kansas City, Kansas City, MO, United States.

Frontiers in pediatrics

|October 14, 2024

概括

结核性肠球炎 (NEC) 的定义正在不断发展,超越了总体术语,以了解特定的疾病类型. 人工智能有助于分类NEC风险因素和新生儿的预后.

科学领域:

新生儿医学新生儿医学
胃肠病学胃肠病学
病理生理学病理生理学

背景情况:

死性肠球炎 (NEC) 是一种严重的疾病,影响新生儿.
目前的NEC定义很广泛,阻碍了了解其多种原因的进展.
五十年的研究强调了对精细分类的需求.

研究的目的:

审查NEC定义和病原学的历史演变.
为了探索NEC内型的概念.
讨论人工智能对NEC研究的影响.

主要方法:

关于NEC定义和病因发生的历史文献综述.
分析目前对NEC内型的理解.
讨论人工智能在新生儿肠道损伤中的应用.

主要成果:

NEC的定义已经从一个通用术语演变为识别不同的病理生理过程 (内型).
人工智能为识别NEC风险因素提供了新的工具.
人工智能有助于分类NEC,并预测新生儿肠道损伤的预后.

结论:

将NEC定义改进为内型是推动临床和研究工作的关键.
人工智能正在改变对NEC和相关新生儿疾病的研究.
更深入地了解NEC表型将改善患者的治疗结果.

关键词:

终极类型终极类型终极类型机器学习是机器学习.死性肠球炎 (necrotizing enterocolitis) 是一种致死性肠球炎的疾病.这是新生儿新生儿.现象型现象型是一种现象型.时间过早的早产.

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