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

推送时:2021-09-16 搜索:次

该报告主题:Debugging hierarchical relations in large biomedical ontologies: finding needles in a haystack

统计人: 崔丽聪

专题讲座准确时间:2021-09-23

讲堂准确时间:11:00

报告模板路线:腾汛研讨会871656108

主办方院校:高中数学与数据统计分析学员

培训讲座人简单:

崔丽聪(http://sbmi.uth.edu/cuilab/index.htm),学土和研究生硕士畢業于河南师范本科院校,硕士畢業于欧美凯斯西储本科院校(Case Western Reserve University),曾任澳大利亚肯塔基大专(University of Kentucky)计算出来机系助手老师,新任德克萨斯二本大学休斯顿绿色有效管理中心(University of Texas Health Science Center at Houston)生活助理专家, 搏士生任课老师,探析方向上为食物临床医学数据信息。在Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Bioinformatics, IEEE Journal of Biomedical and Health Informatics等时代国际职称论文期刊和多媒体发表职称论文职称论文70余篇,Google Scholar引证高达1200次。主管韩国政府清新小学科学新基金的项目3项或者国立环境卫生研究探讨院新项目4项,并直接参与国立环卫钻研院工程项目3项。

专题讲座简价:

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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