The PhD research will investigate efficient ways of applying artificial intelligence in healthcare.
Artificial intelligence and, in particular, machine learning algorithms have proved extremely efficient in dealing with data generated by healthcare practitioners. However, in order to make the best of these approaches, it is important to design the machine learning experiments in a way that is optimal in terms of resources involved and in terms of the accuracy of the results.
In the machine learning community, a test/train split of data is something done in a standard way, mostly random, with a certain distribution. For clinical data, such a split in the experimental phase might not make sense. The data could be split by various attributes: by individual patient, by condition, in a temporal way, and so on. Identifying the right statistical setting for performing the experiments is a challenging task.
There are two challenges that this research will investigate, in a statistical design of artificial intelligence experiments for particular types of clinical data:
- Identifying the best learning method to be applied, together with the optimal parameter setting for it
- Identifying the best learning strategy: which data should be used for training and which for testing
The post holder will work closely with healthcare providers and domain experts.
Doctoral research programmes (PhDs) take a proud place in the world-class research environment and community at Brunel. PhD students are recognised and valued by their supervisors as an essential part of their departments and a key component of the university's overall strategy to develop and deliver world-class research.
A PhD programme is expected to take 3 years full-time or 6 years part-time, with intakes starting in January, April or October.
The general University entrance requirement for registration for a research degree is normally a First or Upper Second Class Honours degree (1st or 2:1) or an international equivalent. A Masters degree is a welcome, but not required, qualification for entry.
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