Similarity Network Fusion: A Novel Application to Making Clinical Diagnoses.

Authors

Andréanne N Zizzo, Western University
Lauren Erdman, University of Toronto
Brian M Feldman, University of Toronto
Anna Goldenberg, University of Toronto

Document Type

Article

Publication Date

5-2018

Journal

Rheumatic Diseases Clinics of North America

Volume

44

Issue

2

First Page

285

Last Page

293

URL with Digital Object Identifier

https://doi.org/10.1016/j.rdc.2018.01.005

Abstract

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.