Deep learning for causal inference on electronic health records

Thesis

Cardiovascular diseases (CVD) are the leading causes of mortality around the world and disentangling cause and effect is central to better understanding and treating these diseases. While randomised clinical trials are the “gold standard” of assessing the effect of an intervention, some hypotheses cannot be feasibly tested in the randomised setting. In these cases, observational studies with appropriate methods of confounding adjustment can deliver reliable evidence concerning the associat...

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Authors: Rao, S

• DOI: 10.5287/ora-5jpno98me
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: electronic health records; causal inference; deep learning
• Subjects: Cardiovascular system--Diseases; Epidemiology; Deep learning (Machine learning)