Applying Ontology and Semantic Web Technologies to Biomedical Research


Thu May 11th 10:00am to 11:00am PDT


Cui Tao PhD


The explosively growing big biomedical data provides enormous opportunities to revolutionize the current clinical practices as well as the biomedical research if the accompanied challenges of heterogeneity in knowledge discovery on biomedical big data can be addressed with novel informatics technologies. Our team has been working on developing semantic technologies to normalize, integrate, query, and analyze the massive volumes of biomedical data as well as to infer new knowledge based on what is known. The core technologies we are developing are based on ontologies and the Semantic Web. Here we share our vision on applying semantic web techniques to clinical knowledge and data representation, as well as to retrieve useful information and knowledge from EHR or online resources. In particular, we will introduce our efforts on (1) representing and normalizing large-scale EHR data in semantic web notations to enable automatic consistency checking and semantic reasoning; (2) temporal information modeling, extraction, and reasoning for patient medical history and time trending analysis; and (3) using semantic queries for patient education.


Dr. Cui Tao an Associate Professor at the University of Texas Health Science Center School of Biomedical Informatics.  Dr. Tao's background is in both Computer Science and biomedical Informatics. She is an expert in medical informatics with focus on conceptual modeling, biomedical ontologies/terminologies, and semantic services. Dr. Tao has been working on applying ontology and semantic web technologies on clinical and translational studies in the past 10 years.  She has extensive experience on ontology development and has been working on developing ontology-based approaches for clinical and biomedical research. She has also been working on consumer informatics focusing on improving consumer health communications using semantic technologies.

Dr. Tao is a recipient of the Presidential Early Career Awards for Scientists and Engineers (PECASE), the highest honor bestowed by the United States Government on science and engineering professionals in the early stages of their independent research careers. Her research findings have been successfully applied to patient data normalization, standard terminology services, as well as clinical, genomic, and pharmacogenomics studies by big research centers and many research projects. She has achieved a productive record and developed innovative semantic technologies for the biomedical domain, which led to more than 100 peer-reviewed papers and 8 invited editorials. Her articles have been cited in over 1,000 publications by researchers from 40 countries. She is currently a PI for two R01 grants and a PI for a BD2K funded U01 grant.


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