Informatics -- Knowledge Management and Data Mining in Biomedicine
Time & Place: Instructor: Jun Ni, Ph.D., Associate Professor Department of Radiology, Carver College of Medicine, Biomedical Engineering Mechanical Engineering University of Iowa, Iowa City, IA, USA Tel: (319) 335-9490 E-mail: jun-ni@uiowa.edu Office Hours and Place: Textbook: Hsinchun Chen, Sherrilynne S. Fuller, Carol Friedman, William Hersh , "Medical Informatics: Knowledge and Data Mining in Biomedicine," by Springer-Verlag New York, 2005       Class Lecture Notes: Additional notes or handouts may be available in classroom. Course Description: this course is primarily designed for researchers and students, biomedical professionals and consultants in the health care industrymedical informatics, computer science, information systems, information science, biomedical, nursing, and pharmaceutical research and practices It covers the basic foundations of the area while extending the foundational material to include the recent leading-edge research in the medical informatics field. The newer concepts, techniques, and practices of biomedical knowledge management and data mining are introduced and examined in detail. It covers the research and applications in these areas that are raising the technical horizons and expanding the utility of informatics to an increasing number of biomedical professionals and researchers. The course has three sections Section I presents the foundational information and knowledge management material and includes topics such as: bioinformatics challenges and standards, security and privacy, ethical and social issues, and biomedical knowledge mapping. Section II discusses the topics which are relevant to knowledge representations & access and includes topics such as: representations of medical concepts and relationships, genomic information retrieval, 3D medical informatics, public access to anatomic images, and creating and maintaining biomedical ontologies. Section III examines the emerging application research in data mining, biomedical textual mining, and knowledge discovery research and includes topics such as: semantic parsing and analysis for patient records, biological relationships, gene pathways, and metabolic networks, exploratory genomic data analysis, joint learning using data and text mining, and disease informatics and outbreak detection. The course is a comprehensive presentation of the foundations and leading application research in medical informatics/biomedicine. These concepts and techniques are illustrated with detailed case studies. Pre-requisites: TBD Course Contents: Introduction to Medical Informatics Mapping Medical Informatics Research Bioinformatics Challenges Medical Concept Representation Standards in Medical Informatics Information Retrieval and Digital Library Genomics Information Retrieval Managing Information Security and Privacy in Health Care Ethical and Social Challenges in Medical Informatics.- Characterizing Biomedical Concept Relationships Anatomic Images for the Public -3D Medical Informatics Medical Ontologies Semantic Parsing and Knowledge Representation in Biomedicine Semantic Text Parsing for Patient Records Identification of Biological Relationships from Text Documents Creating, Modeling and Visualizing Metabolic Networks: FCModeler and PathBinder for Network Modeling and Creation Gene Pathway Text Mining and Visualization The Genomic Data Mine Exploratory Genomic Data Analysis Joint Learning Using Data and Text Mining Disease Informatics and Outbreak Detection

 

Hawkeye Radiology Informatics (HawkRI)
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