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Thesis

Methods of classification of the cardiotocogram

Abstract:

This Thesis compares CTG classification techniques proposed in the literature and their potential extensions. A comparison between four classifiers previously assessed - Adaboost, Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machine (SVM) - and two proposed classifiers - Bayesian ANN (BANN), Relevance Vector Machine - was conducted using a database of 7,568 cases and two open source databases. The Random Forest (RF) achieved the highest average result and was propos...

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Department:
University of Oxford
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University of Oxford
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Grant:
EP/G036861/1
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Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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