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The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord
Includes bibliographical references (leaves 120-128).
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Division of Biomedical Engineering
2014
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| _version_ | 1867613261257506816 |
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| access_status_str | Open Access |
| author | Alhamud, Alkathafi Ali |
| author2 | Capper, Wayne |
| author_browse | Alhamud, Alkathafi Ali Capper, Wayne |
| author_facet | Capper, Wayne Alhamud, Alkathafi Ali |
| author_sort | Alhamud, Alkathafi Ali |
| collection | Thesis |
| description | Includes bibliographical references (leaves 120-128). |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/3220 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:33:19.547Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Division of Biomedical Engineering |
| publisherStr | Division of Biomedical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/3220 The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord Alhamud, Alkathafi Ali Capper, Wayne Vaughan, Christopher Leonard (Kit) Biomedical Engineering Includes bibliographical references (leaves 120-128). Present-day obstetric decision-making is based on measuring the umbilical arterial blood flow velocity waveforms from one site of the cord. There is an ongoing debate on the predictive value of Doppler measurements in the evaluation of the foetal condition. The aim of this thesis is to investigate the use ofa neural network to recognise blood flow waveform shape patterns associated with placental insufficiency. Eleven backpropagation neural networks have been developed and trained based on the waveforms that are generated from the foetal mathematical model (developed in previous research) at both ends of the cord. Only two networks trained successfully. These two networks are the Levenberg-Marquardt algorithm (Trainlm) and the resilient backpropagation algorithm (Trainrp). 2014-07-28T18:15:55Z 2014-07-28T18:15:55Z 2005 Master Thesis Masters MSc http://hdl.handle.net/11427/3220 eng application/pdf Division of Biomedical Engineering Faculty of Health Sciences University of Cape Town |
| spellingShingle | Biomedical Engineering Alhamud, Alkathafi Ali The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| thesis_degree_str | Master's |
| title | The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| title_full | The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| title_fullStr | The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| title_full_unstemmed | The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| title_short | The use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| title_sort | use of a neural network to recognize placental insufficiency from blood flow velocity waveforms in the umbilical cord |
| topic | Biomedical Engineering |
| url | http://hdl.handle.net/11427/3220 |
| work_keys_str_mv | AT alhamudalkathafiali theuseofaneuralnetworktorecognizeplacentalinsufficiencyfrombloodflowvelocitywaveformsintheumbilicalcord AT alhamudalkathafiali useofaneuralnetworktorecognizeplacentalinsufficiencyfrombloodflowvelocitywaveformsintheumbilicalcord |