Time Models in Patient-Generated Content

Student: Kondrateva Anna

Supervisor: Irina Efimenko

Educational Programme: Fundamental and Computational Linguistics (Bachelor)

Final Grade: 9

Year of Graduation: 2019

Automatic extraction of medical events (e.g. operations or treatments) from a patient-generated content (e.g. messages from online health forums) and anchoring them to a timeline can be extremely useful for purposes of diagnostics and retrospective clinical studies. There are existing systems which are able to extract temporal information from clinical data and show acceptable results, but these systems currently work only with English data and well-structured, specialist-generated content (e.g. health records). This study is focused on working on the first stage of developing such system which is able to process Russian patient-generated content. The research suggests an analysis of specificities and limitations related to this particular type of data, classification of temporal information that can be extracted from the data and extensions for TimeML markup language.

Full text (added June 4, 2019)

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