Using Deep Learning with Canadian Primary Care Data for Disease Diagnosis-Reference-Cited by-同舟云学术

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Using Deep Learning with Canadian Primary Care Data for Disease Diagnosis

Published:2021 Issue: Volume: Page:273-310
ISSN:
Container-title:Deep Learning for Biomedical Data Analysis
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Author:

Zafari Hasan,Kosowan Leanne,Lam Jason T.,Peeler William,Gasmallah Mohammad,Zulkernine Farhana,Singer Alexander

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-71676-9_12

Reference132 articles.

1. Chang, F., & Gupta, N. (2015). Progress in electronic medical record adoption in Canada. Canadian Family Physician, 61(12), 1076-1084.

2. Marrie, R. A., Kosowan, L., Taylor, C., & Singer, A. (2019). Identifying people with multiple sclerosis in the Canadian primary care sentinel surveillance network. Multiple Sclerosis Journal–Experimental, Translational and Clinical

3. Cave, A. J., Davey, C., Ahmadi, E., Drummond, N., Fuentes, S., Kazemi-Bajestani, S. M. R., ... & Taylor, M. (2016). Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records. NPJ primary care respiratory medicine, 26(1), 1-4.

4. Kosowan, L., Wicklow, B., Queenan, J., Yeung, R., Amed, S., & Singer, A. (2019). Enhancing Health Surveillance: Validation of a Novel Electronic Medical Records-Based Definition of Cases of Pediatric Type 1 and Type 2 Diabetes Mellitus. Canadian journal of diabetes, 43(6), 392-398.

5. Williamson, T., Green, M. E., Birtwhistle, R., Khan, S., Garies, S., Wong, S. T., ... & Drummond, N. (2014). Validating the 8 CPCSSN case definitions for chronic disease surveillance in a primary care database of electronic health records. The Annals of Family Medicine, 12(4), 367-372.

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