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Dr. Tawfik: Text Mining for Precision Medicine

posted Nov 25, 2020, 6:37 AM by Marco Spruit   [ updated Nov 25, 2020, 6:38 AM ]
Yesterday Noha Tawfik defended her dissertation Text Mining for Precision Medicine: Natural Language Processing, Machine Learning and Information Extraction for Knowledge Discovery in the Health Domain. In extreme COVID19 style, we were with merely 8 people --including audience-- in the Senate Hall of the UU Academiegebouw. Nevertheless, Noha admirably competently and passionately defended her PhD research!

In Noha's first research phase, she mainly employed Information Extraction to automate the identification and analysis of Genome-Wide Association Studies, given a particular disease, to investigate the relation between different phenotypic traits and Single Nucleotide Polymorphisms, known to be associated with that disease. In the second research phase, Noha expands upon the previous work by employing Machine Learning algorithms to the problem of detecting contradictions between two statements, extracted from abstracts of published articles. interpreting contradictory findings as a likely Precision Medicine finding. In the third and final phase of her research, Noha her contradiction detection research in conformance with Natural Language Inference (NLI) best practices, and participated in the 2019 ACL "Medical Natural Language Inference" challenge where she battled successfully against entire teams of various top universities.

All in all a truly excellent achievement in 4 years time with no less than 7 peer-reviewed publications!
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