Text Mining the History of Medicine
Sophia Ananiadou
University of Manchester
I will present the results of a collaborative and interdisciplinary project between the National Centre for Text Mining (NaCTeM) and the Centre for the History of Science, Technology and Medicine (CHSTM) at the University of Manchester, demonstrating the capabilities of innovative text mining tools to allow the automatic extraction of information from two historical archives: the British Medical Journal (BMJ) (1840 - present) and the London-area Medical Officer of Health (MOH) reports (1848-1972). Using a new semantically annotated corpus of historical medical text, NaCTeM's text mining tools have been adapted to recognise information that is pertinent to historical medical research. The adapted tools have been used to automatically enrich the entire contents of the two historical archives with semantic metadata, i.e., terms, named entities and events. The resulting semantic information has been used to develop semantic search system over the archives, which assists uses to expand their queries with (possibly time-sensitive) related terms, facilitates tracking of terminology usage over time and allows search results to be refined according to the presence of named entities and/or events.