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新生儿坏死性小肠结肠炎风险因素及风险评估的研究进展
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Abstract:
坏死性小肠结肠炎(NEC)是一种严重威胁新生儿尤其是早产儿的胃肠道急症。低出生胎龄、低出生体重是NEC最显著的危险因素之一。母乳喂养、采取标准化喂养方案、使用益生菌有利于降低NEC发生风险。目前已有不少关于NEC风险评估相关工具，大多利用回顾性研究数据且采用建模的方法，其有效性仍需要多中心前瞻性试验来验证。近些年机器学习整合多组学数据集的方法取得了重大进展。使用机器学习工具和算法，可以将多组学数据与临床信息相结合以开发预测模型。机器学习工具整合多组学和临床数据将为精准医学铺平道路。
Necrotizing enterocolitis (NEC) is a serious gastrointestinal disease especially in premature infants. Low gestational age and birth weight are the highest risk factors for NEC. Feeding of breast milk, use of standardized feeding guidelines and probiotics reduce NEC risk. At present, there are many tools for necrotizing enterocolitis risk assessment of which use retrospective study data modeling. How-ever, their effectiveness needs to be validated by multicenter prospective study. Significant ad-vances have been achieved in the integration methods of these multiomics data sets by machine learning. Using machine learning tools and algorithms, it is possible to integrate multiomics data with clinical information to develop predictive models. Leveraging machine learning tools for inte-gration of multiomics and clinical data will pave the way for precision medicine.
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