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Fusion of clinical data: A case study to predict the type of treatment of bone fractures

Author
Haq, A.; Wilk, S.; Abello, A.
Type of activity
Journal article
Journal
International journal of applied mathematics and computer science
Date of publication
2019-03-29
Volume
29
Number
1
First page
51
Last page
67
DOI
10.2478/amcs-2019-0004
Repository
http://hdl.handle.net/2117/134366 Open in new window
URL
https://content.sciendo.com/view/journals/amcs/29/1/article-p51.xml Open in new window
Abstract
A prominent characteristic of clinical data is their heterogeneity—such data include structured examination records and laboratory results, unstructured clinical notes, raw and tagged images, and genomic data. This heterogeneity poses a formidable challenge while constructing diagnostic and therapeutic decision models that are currently based on single modalities and are not able to use data in different formats and structures. This limitationmay be addressed using data fusion methods. In this...
Citation
Haq, A.; Wilk, S.; Abelló, A. Fusion of clinical data: A case study to predict the type of treatment of bone fractures. "International journal of applied mathematics and computer science", 29 Març 2019, vol. 29, núm. 1, p. 51-67.
Keywords
Clinical data, Combination of data, Combination of interpretation, Data fusion, Decision support, Prediction models
Group of research
DTIM - Database Technologies and lnformation Management Group
inLab FIB
inSSIDE - integrated Software, Service, Information and Data Engineering

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