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Thesis

Machine learning for childhood pneumonia diagnosis

Abstract:

Pneumonia is the number one killer of children under the age of 5, causing more deaths than malaria, tuberculosis and HIV/AIDS combined. In 2015, over 920,000 children died of pneumonia and more than 95% of the incidence and 99% of subsequent mortality occurred in developing countries. Current gold standard diagnostic assessment of childhood pneumonia relies on the use of advanced tools (such as X-rays and blood culture) by a clinical expert who assesses and interprets a combination of cli...

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Supervisor
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Grant:
EP/G036861/1
Funding agency for:
Project
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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