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Biomedical Text Mining: Structuring the Unstructured

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If you have a question about this talk, please contact Mohammad Taher Pilehvar.

How can we capture information from biomedical text as conveniently as accessing a database? In this talk we will look at some of the challenges in processing diverse biomedical documents including scientific literature and electronic medical records. In addition to syntactic and semantic challenges, we will discuss the challenges of embedded tables and document structure.

Many of these challenges have been addressed over the last 15 years within the agile text mining platform, I2E , allowing a wide range of practical applications in both the pharmaceutical industry and healthcare. The talk will conclude by showing how normalisation of concepts and relationships allows direct selection of patients using criteria such as “between 18 and 65 years old, have cancer, weigh over 200lbs, and have a specific gene mutation”.

This talk is part of the Language Technology Lab Seminars series.

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