Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
Development of Diagnostic System for FHR Monitering by Using Neural Networks
- Issue Date
- Jan-2006
- Publisher
- 한국통계학회
- Keywords
- Fetal heart rete (FHR); Approximate entropy; Neural networks.
- Citation
- Communications for Statistical Applications and Methods, v.13, no.1, pp 73 - 88
- Pages
- 16
- Indexed
- KCI
- Volume
- 13
- Number
- 1
- Start Page
- 73
- End Page
- 88
- ISSN
- 2287-7843
- Abstract
- In this paper, we construct data-base for fetal heart rate (FHR) data and develop the FHR Monitering system to diagnose fetus, HYFM-Ⅲ. For diagnostic system, a few statistical decision making mechanism are adopted, such as approximate entropy, neural networks, and logistic discrimination. Since FHR data is very chaotic, we mostly adopt nonlinear statistical methods. On the basis of this system, we expect to expert system for early detection of abnormal fetus.
- Files in This Item
- Go to Link
- Appears in
Collections - 서울 자연과학대학 > 서울 수학과 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Related Researcher
- Park, Young Sun
- COLLEGE OF NATURAL SCIENCES (DEPARTMENT OF MATHEMATICS)