An artificial neural network model for the evaluation of carotid artery stenting prognosis using a national-wide database

Chun An Cheng, Hung Wen Chiu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Stroke is a serious health problem in many countries. About 20% of ischemia stroke involves carotid stenosis. Neck carotid ultrasound is fast, secure and convenient way to detect carotid artery stenosis. Carotid artery stenting (CAS) has become a popular treatment for cerebrovascular stenosis in recent years. However, CAS may also induce the occurrence of major adverse cardiovascular events (MACE) in older patients. Hence the evaluation the CAS prognosis is important.

Original languageEnglish
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2566-2569
Number of pages4
ISBN (Electronic)9781509028092
DOIs
Publication statusPublished - Sep 13 2017
Externally publishedYes
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: Jul 11 2017Jul 15 2017

Other

Other39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
CountryKorea, Republic of
CityJeju Island
Period7/11/177/15/17

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ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Cheng, C. A., & Chiu, H. W. (2017). An artificial neural network model for the evaluation of carotid artery stenting prognosis using a national-wide database. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings (pp. 2566-2569). [8037381] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2017.8037381