The utilisation of dynamic neural networks for medical data classifications-survey with case study

Abir Jaafar Hussain; Paul Fergus; Dhiya D. Al-Jumeily; Haya Alaskar; Naeem Radi

doi:10.1007/978-3-319-22053-6_80

The utilisation of dynamic neural networks for medical data classifications-survey with case study

Abir Jaafar Hussain
, Paul Fergus
, Dhiya D. Al-Jumeily
, Haya Alaskar
, Naeem Radi

Computer Sciences

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Various recurrent neural networks have been utilised for medical data analysis and classifications. In this paper, the ability of using dynamic neural network to medicine related problems has been examined. Furthermore, a survey on the use of recurrent neural network architectures in medical applications will be discussed. A case study using the Elman, the Jordan and Layer recurrent networks for the classifications of Uterine Electrohysterography signals for the prediction of term and preterm delivery for pregnant women are presented.

Original language	English
Pages (from-to)	752-758
Number of pages	7
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9227
DOIs	https://doi.org/10.1007/978-3-319-22053-6_80
State	Published - 2015
Event	11th International Conference on Intelligent Computing, ICIC 2015 - Fuzhou, China Duration: 20 Aug 2015 → 23 Aug 2015

Keywords

Dynamic neural network
Features extraction
Uterine EMG signals

Access to Document

10.1007/978-3-319-22053-6_80

Cite this

Jaafar Hussain, A., Fergus, P., Al-Jumeily, D. D., Alaskar, H., & Radi, N. (2015). The utilisation of dynamic neural networks for medical data classifications-survey with case study. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9227, 752-758. https://doi.org/10.1007/978-3-319-22053-6_80

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abstract = "Various recurrent neural networks have been utilised for medical data analysis and classifications. In this paper, the ability of using dynamic neural network to medicine related problems has been examined. Furthermore, a survey on the use of recurrent neural network architectures in medical applications will be discussed. A case study using the Elman, the Jordan and Layer recurrent networks for the classifications of Uterine Electrohysterography signals for the prediction of term and preterm delivery for pregnant women are presented.",

keywords = "Dynamic neural network, Features extraction, Uterine EMG signals",

author = "\{Jaafar Hussain\}, Abir and Paul Fergus and Al-Jumeily, \{Dhiya D.\} and Haya Alaskar and Naeem Radi",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 11th International Conference on Intelligent Computing, ICIC 2015 ; Conference date: 20-08-2015 Through 23-08-2015",

year = "2015",

doi = "10.1007/978-3-319-22053-6\_80",

language = "English",

volume = "9227",

pages = "752--758",

journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Jaafar Hussain, A, Fergus, P, Al-Jumeily, DD, Alaskar, H & Radi, N 2015, 'The utilisation of dynamic neural networks for medical data classifications-survey with case study', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9227, pp. 752-758. https://doi.org/10.1007/978-3-319-22053-6_80

The utilisation of dynamic neural networks for medical data classifications-survey with case study. / Jaafar Hussain, Abir; Fergus, Paul; Al-Jumeily, Dhiya D. et al.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 9227, 2015, p. 752-758.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - The utilisation of dynamic neural networks for medical data classifications-survey with case study

AU - Jaafar Hussain, Abir

AU - Fergus, Paul

AU - Al-Jumeily, Dhiya D.

AU - Alaskar, Haya

AU - Radi, Naeem

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Various recurrent neural networks have been utilised for medical data analysis and classifications. In this paper, the ability of using dynamic neural network to medicine related problems has been examined. Furthermore, a survey on the use of recurrent neural network architectures in medical applications will be discussed. A case study using the Elman, the Jordan and Layer recurrent networks for the classifications of Uterine Electrohysterography signals for the prediction of term and preterm delivery for pregnant women are presented.

AB - Various recurrent neural networks have been utilised for medical data analysis and classifications. In this paper, the ability of using dynamic neural network to medicine related problems has been examined. Furthermore, a survey on the use of recurrent neural network architectures in medical applications will be discussed. A case study using the Elman, the Jordan and Layer recurrent networks for the classifications of Uterine Electrohysterography signals for the prediction of term and preterm delivery for pregnant women are presented.

KW - Dynamic neural network

KW - Features extraction

KW - Uterine EMG signals

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U2 - 10.1007/978-3-319-22053-6_80

DO - 10.1007/978-3-319-22053-6_80

M3 - Conference article

AN - SCOPUS:84983620692

SN - 0302-9743

VL - 9227

SP - 752

EP - 758

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

T2 - 11th International Conference on Intelligent Computing, ICIC 2015

Y2 - 20 August 2015 through 23 August 2015

ER -

The utilisation of dynamic neural networks for medical data classifications-survey with case study

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Keywords

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