Improving Deep Learning Classifier for Fetus Hypoxia Detection in Cardiotocography Signal-Reference-Cited by-同舟云学术

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Improving Deep Learning Classifier for Fetus Hypoxia Detection in Cardiotocography Signal

Published:2019-10 Issue: Volume: Page:
ISSN:
Container-title:2019 International Workshop on Big Data and Information Security (IWBIS)
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Author:

Ma'sum M. Anwar,Riskyana Dewi Intan P,Jatmiko Wisnu,Krisnadhi Adila Alfa,Setiawan Noor Akhmad,Suarjaya I Made Agus Dwi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8932634/8935669/08935835.pdf?arnumber=8935835

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Diagnosis of cardiotocographic sinusoidal patterns by spectral analyses;Biomedical Signal Processing and Control;2024-07

2. Fetal Hypoxia Detection Using Machine Learning: A Narrative Review;AI;2024-04-13

3. Exploring Effective Approaches on Transformer-Based Neural Models for Multi-clinical Large-Scale Cardiotocogram Data;IFMBE Proceedings;2024

4. ML-Based Interpretation of Cardiotocography Data: Current State and Future Research;2023 International Conference of Computer Science and Information Technology (ICOSNIKOM);2023-11-10

5. Real-time Classification of Fetal Status Based on Deep Learning and Cardiotocography Data;Journal of Medical Systems;2023-08-03

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