A new approach to distinguish migraine from stroke by mining structured and unstructured clinical data-sources-Reference-Cited by-同舟云学术

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A new approach to distinguish migraine from stroke by mining structured and unstructured clinical data-sources

Published:2016-10-06 Issue:1 Volume:5 Page:
ISSN:2192-6662
Container-title:Network Modeling Analysis in Health Informatics and Bioinformatics
language:en
Short-container-title:Netw Model Anal Health Inform Bioinforma

Author:

Sedghi Elham,Weber Jens H,Thomo Alex,Bibok Maximilian,Penn Andrew M. W.

Funder

The Heart and Stroke Fund of Canada/CIHR

Genome Canada/BC

Publisher

Springer Science and Business Media LLC

Subject

Urology

Link

http://link.springer.com/content/pdf/10.1007/s13721-016-0137-2.pdf

Reference24 articles.

1. Arauzo-Azofra A, Benitez JM, Castro JL (2008) Consistency measures for feature selection. J Intell Inf Syst 30(3):273–292

2. Cao ZH, Ko LW, Lai KL, Huang SB, Wang SJ, Lin CT (2015) Classification of migraine stages based on resting-state eeg power. In: 2015 international joint conference on neural networks (IJCNN), IEEE, pp 1–5

3. Duval B, Hao JK, Hernandez Hernandez JC (2009) A memetic algorithm for gene selection and molecular classification of cancer. In: Proceedings of the 11th annual conference on genetic and evolutionary computation. ACM, New York, pp 201–208

4. Etminan M, Takkouche B, Isorna FC, Samii A et al (2005) Risk of ischaemic stroke in people with migraine: systematic review and meta-analysis of observational studies. BMJ 330(7482):63

5. Ghandehari K, Ashrafzadeh F, Mood ZI, Ebrahimzadeh S, Arabikhan K (2012) Development and validation of the asian migraine criteria (AMC). J Clin Neurosci 19(2):224–228

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1. Role and Challenges of Unstructured Big Data in Healthcare;Data Management, Analytics and Innovation;2019-10-25

2. Clinical text classification research trends: Systematic literature review and open issues;Expert Systems with Applications;2019-02

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