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Thesis

Bayesian fusion of continuous-valued labels in biomedical applications

Abstract:

Expert labelling is the gold standard for diagnosing patient-specific diseases from medical data. However, experts are relatively scarce, their time is expensive, and the task of labelling is time-consuming. While automated algorithms offer advantages of time efficiency, repeatability, and cost-saving benefits compared to manual labelling, there remains a substantial discrepancy in their estimation as well as reliability that limit their use.

Two commonly-encountered and clinica...

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Division:
MSD
Department:
Nuffield Department of Population Health
Department:
Engineering Science
Role:
Author

Contributors

Department:
Engineering Science
Role:
Supervisor
Department:
Emory University
Role:
Supervisor


DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford


UUID:
uuid:2d449f57-4e1d-45a0-8aca-143a2590192a
Deposit date:
2016-10-24
ARK identifier:

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