相似性网络融合：一种用于临床诊断的新应用。
Similarity Network Fusion: A Novel Application to Making Clinical Diagnoses.
作者信息
Zizzo Andréanne N, Erdman Lauren, Feldman Brian M, Goldenberg Anna
机构信息
Department of Pediatrics, Division of Gastroenterology and Hepatology, Western University, Children's Hospital, London Health Sciences Centre, 800 Commissioners Road East, B1-162, London, Ontario N6A 5W9, Canada.
Genetics and Genome Biology, Department of Computer Science, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning (PGCRL), University of Toronto, 686 Bay Street, Toronto, Ontario M5G 0A4, Canada.
出版信息
Rheum Dis Clin North Am. 2018 May;44(2):285-293. doi: 10.1016/j.rdc.2018.01.005. Epub 2018 Feb 21.
Similarity Network Fusion (SNF) is a novel methodological tool that integrates multiple different types of data to identify homogeneous subsets of patients in whom disease classification may be otherwise unclear or challenging. In this review article, the authors hope to provide insight into how SNF can be used in clinical decision making where the aim is to have little influence on the data prior to obtaining the results of the analysis.
相似性网络融合（SNF）是一种新颖的方法工具，它整合多种不同类型的数据，以识别疾病分类可能不明确或具有挑战性的患者的同质子集。在这篇综述文章中，作者希望深入探讨SNF如何用于临床决策，其目的是在获得分析结果之前对数据的影响最小。
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