The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network
المؤلفون المشاركون
Yang, Xu
Wang, Taoyi
Tang, Haijing
Li, Mengke
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-12-03
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Mobile medical care is a hot issue in current medical research.
Due to the inconvenience of going to hospital for fetal heart monitoring and the limited medical resources, real-time monitoring of fetal health on portable devices has become an urgent need for pregnant women, which helps to protect the health of the fetus in a more comprehensive manner and reduce the workload of doctors.
For the feature acquisition of the fetal heart rate (FHR) signal, the traditional feature-based classification methods need to manually read the morphological features from the FHR curve, which is time-consuming and costly and has a certain degree of calibration bias.
This paper proposes a classification method of the FHR signal based on neural networks, which can avoid manual feature acquisition and reduce the error caused by human factors.
The algorithm will directly learn from the FHR data and truly realize the real-time diagnosis of FHR data.
The convolution neural network classification method named “MKNet” and recurrent neural network named “MKRNN” are designed.
The main contents of this paper include the preprocessing of the FHR signal, the training of the classification model, and the experiment evaluation.
Finally, MKNet is proved to be the best algorithm for real-time FHR signal classification.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Tang, Haijing& Wang, Taoyi& Li, Mengke& Yang, Xu. 2018. The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1132210
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Tang, Haijing…[et al.]. The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1132210
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Tang, Haijing& Wang, Taoyi& Li, Mengke& Yang, Xu. The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1132210
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1132210
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر