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Debugging hierarchical relations in large biomedical ontologies: finding needles in a haystack

發(fā)布時間:2021-09-16 瀏覽:

報告題目:Debugging hierarchical relations in large biomedical ontologies: finding needles in a haystack

報告人: 崔麗聰

講座日期:2021-09-23

講座時間:11:00

報告地點:騰訊會議871656108

主辦單位:數(shù)學與統(tǒng)計學院

講座人簡介:

崔麗聰(https://sbmi.uth.edu/cuilab/index.htm),學士和碩士畢業(yè)于陜西師范大學,博士畢業(yè)于美國凱斯西儲大學(Case Western Reserve University),曾任美國肯塔基大學(University of Kentucky)計算機系助理教授,現(xiàn)任德克薩斯大學休斯頓健康科學中心(University of Texas Health Science Center at Houston)助理教授, 博士生導師,研究方向為生物醫(yī)學信息。在Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Bioinformatics, IEEE Journal of Biomedical and Health Informatics等國際期刊和會議發(fā)表論文70余篇,Google Scholar引用超過1200次。主持美國國家自然科學基金項目3項以及國立衛(wèi)生研究院項目4項,并參與國立衛(wèi)生研究院項目3項。

講座簡介:

Ontologies have been used in a wide variety of biomedical applications including information extraction and retrieval, data integration and management, clinical decision support. Quality defects of biomedical ontologies, if not addressed, could affect all downstream applications that use them as knowledge sources. However, identification of potential quality defects is challenging due to the ever-growing size and complexity of biomedical ontologies (i.e., large and evolving graphs). We develop principled and machine learning-based approaches to effectively detect missing or erroneous hierarchical relations in large ontologies including SNOMED CT and Gene Ontology.

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