Biomedical Natural Language Processing Lab

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Biomedical Natural Language Processing Lab

Biomedical Natural Language Processing Lab

The Natural Language Processing group at the School of Biomedical Informatics aims to facilitate biomedical discovery by developing, evaluating, and applying novel informatics methods and software to extract, compile and analyze heterogeneous biomedical data. Led by Dr. Hua Xu, the team of faculty, research scientists, postdocs, programmers and students focus on NLP and data mining of clinical data in three specific areas. The work encompasses basic research in clinical NLP involving to software development and applications for specific biomedical problems.

 

The group has worked on a variety of challenges faced in the clinical NLP domain including Named entity recognition, Word sense disambiguation, Semantic role labeling, Syntactic parsing, Active learning and Deep learning. Many of the algorithms developed by members of the team were submitted to Challenges in the clinical and biomedical NLP domains and are ranked in the top two positions.

 

These state-of-the-art methods and algorithms form the basis for a variety of software developed in the group. The developed software is made openly available to the academic community and includes MedEx (https://sbmi.uth.edu/ccb/resources/medex.htm), CARD (https://sbmi.uth.edu/ccb/resources/abbreviation.htm) and CLAMP (clinical language annotation, modeling and processing)( http://clamp.uth.edu/). The NLP software developed in the lab have also been widely adopted by the community.

 

Further, both the algorithms and their implementations have been extensively used for biomedical applications such as clinical and translational studies based on EHRs. Some of the representative applications that were researched by the team are post-marketing surveillance for drugs, pharmacogenomics, cancer epidemiology and healthcare analytics. Many of our studies have served as models for using EHRs and informatics approaches to efficiently and inexpensively conduct successful clinical, genomic, and pharmacogenomic research.

 

The Xu lab is well-funded with current funding to the tune of approximately $ 7.5 million. Members of the lab are also extensively involved in collaborative projects with researchers both nationally and at the international level. Graduate students, postdocs and other students (such as masters students, interns etc) as well as visiting scientists form an integral part of the team with their training being a continuing focus in the group in addition to research work.