25 - 29 June 2018
This 5 day course is aimed at post-graduate research students and researchers from both applied health sciences and computer science who have come up against the problem that much medical and biomedical data is held in unstructured, textual form, and who wish to handle this data computationally.
The secondary use of Electronic Health Records (EHRs) has transformative potential for how healthcare research is conducted, yielding new possibilities in areas of business intelligence, observational research, clinical trial recruitment and decision support. However, as much as 80% of the data in the EHR are known to be locked in the form of unstructured text, making this information 'invisible' for standard analysis techniques. In addition, this course will convey an appreciation of the complexity that different NLP problems pose, via a series of talks and practical sessions. The course will also cover the concept of hierarchical concepts and ontologies, and their role in adding semantically meaningful knowledge into NLP applications.
The course is relevant to researchers from all areas of applied health looking to incorporate text mining and natural language processing in to their research. It is also relevant to computer scientists collaborating or providing support in an applied health setting. A numerate undergraduate degree is required. Although not necessary, some computer programming experience would be helpful.
Academic Lead: Angus Roberts, Senior Lecturer in Health Informatics
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Cost: £500 (KHP discounts available)