MEDICAL INFORMATICS Knowledge Management and Data Mining in Biomedicine ppt

MEDICAL INFORMATICS Knowledge Management and Data Mining in Biomedicine INTEGRATED SERIES IN INFORMATION SYSTEMS Series Editors Professor Ramesh Sharda Prof. Dr. Stefan Vo13 Oklahoma State University Universitat Hamburg Other published titles in the series: E-BUSINESS MANAGEMENT: Integration of Web Technologies with Business Models1 Michael J. Shaw VIRTUAL CORPORATE UNIVERSITIES: A Matrix of Knowledge and Learning for the New Digital DawdWalter R.J. Baets & Gert Van der Linden SCALABLE ENTERPRISE SYSTEMS: An Introduction to Recent Advances1 edited by Vittal Prabhu, Soundar Kumara, Manjunath Kamath LEGAL PROGRAMMING: Legal Compliance for RFID and Software Agent Ecosystems in Retail Processes and Beyond1 Brian Subirana and Malcolm Bain LOGICAL DATA MODELING: What It Is and How To Do It1 Alan Chmura and J. Mark Heumann DESIGNING AND EVALUATING E-MANAGEMENT DECISION TOOLS: The Integration of Decision and Negotiation Models into Internet-Multimedia Technologies1 Giampiero E.G. Beroggi INFORMATION AND MANAGEMENT SYSTEMS FOR PRODUCT CUSTOMIZATIONI Blecker, Friedrich, Kaluza, Abdelkafi & Kreutler MEDICAL INFORMATICS Knowledge Management and Data Mining in Biomedicine edited by Hsinchun Chen Sherrilynne S . Fuller Carol Friedman William Hersh Springer - Hsinchun Chen Sherrilynne S. Fuller The University of Arizona, USA University of Washington, USA Carol Friedman William Hersh Columbia University, USA Oregon Health & Science Univ., USA Library of Congress Cataloging-in-Publication Data A C.I.P. Catalogue record for this book is available from the Library of Congress. ISBN-10: 0-387-2438 1-X (HB) ISBN- 10: 0-387-25739-X (e-book) ISBN- 13: 978-0387-2438 1-8 (HB) ISBN- 13: 978-0387-25739-6 (e-book) O 2005 by Springer Science+Business Media, Inc. All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science + Business Media, Inc., 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now know or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks and similar terms, even if the are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed in the United States of America. 98765432 1 SPIN 1 1055556 TABLE OF CONTENTS Editors' Biographies xix Authors' Biographies xxiii Preface xxxix UNIT I: Foundational Topics in Medical In formatics Chapter 1: Knowledge Management. Data Mining. and Text Mining in Medical Informatics 3 Introduction 5 Knowledge Management, Data Mining, and Text Mining: An Overview 6 2.1 Machine Learning and Data Analysis Paradigms 7 2.2 Evaluation Methodologies 11 Knowledge Management, Data Mining, and Text Mining Applications in Biomedicine 12 3.1 Ontologies 13 3.2 Knowledge Management 14 3.3 Data Mining and Text Mining 18 3.4 Ethical and Legal Issues for Data Mining 22 Summary 22 References 23 Suggested Readings 31 Online Resources 31 Questions for Discussion 33 Chapter 2: Mapping Medical Informatics Research 35 1 . Introduction 37 2 . Knowledge Mapping: Literature Review 37 3 . Research Design 39 3.1 Basic Analysis 39 3.2 Content Map Analysis 40 3.3 Citation Analysis 41 4 . Data Description 42 5 . Results 44 5.1 Basic Analysis 44 5.2 Content Map Analysis 47 5.3 Citation Network Analysis 55 6 . Conclusion and Discussion 57 7 . Acknowledgement 58 References 58 Suggested Readings 60 Online Resources 61 Questions for Discussion 61 Chapter 3: Bioinformatics Challenges and Opportunities 63 1 . Introduction 65 2 . Overview of the Field 69 2.1 Definition of Bioinformatics 69 2.2 Opportunities and Challenges - Informatics Perspective 70 2.3 Opportunities and Challenges - Biological Perspective 79 3 . Case Study 83 3.1 Informatics Perspective - The BIOINFOMED Study and Genomic Medicine 83 3.2 Biological Perspective - The BioResearch Liaison Program at the University of Washington 85 4 . Conclusions and Discussion 89 5 . Acknowledgements 91 References 91 Suggested Readings 92 Online Resources 93 Questions for Discussion 93 Chapter 4: Managing Information Security and Privacy in Health Care Data Mining: State of the Art 95 1 . Introduction 97 . 2 Overview of Health Information Privacy and Security 98 2.1 Privacy and Healthcare Information 99 2.2 Security and Healthcare Information 99 3 . Review of the Literature: Data Mining and Privacy and Security 109 vii 3.1 General Approaches to Assuring Appropriate Use 110 3.2 Specific Approaches to Achieving Data Anonymity 112 3.3 Other Issues in Emerging "Privacy Technology" 116 3.4 "Value Sensitive Design": A Synthetic Approach to Technological Development 117 3.5 Responsibility of Medical Investigators 119 4 . Case Study: The Terrorist Information Awareness Program (TIA) 12 1 4.1 The Relevance of TIA to Data Mining in Medical Research 121 4.2 Understanding TIA 122 4.3 Controversy 124 4.4 Lessons Learned from TIA's Experience for Medical Investigators Using "Datamining" Technologies 128 5 . Conclusions and Discussion 129 6 . Acknowledgements 131 References 131 Suggested Readings 134 Online Resources 135 Questions for Discussion 13 7 Chapter 5: Ethical and Social Challenges of Electronic Health Information 139 1 . Introduction 141 2 . Overview of the Field 142 2.1 Electronic Health Records 142 2.2 Clinical Alerts and Decision Support 146 2.3 Intemet-based Consumer Health Information 150 2.4 Evidence-based Medicine, Outcome Measures. and Practice Guidelines 152 2.5 Data Mining 153 References 156 Suggested Readings 157 Online Resources 157 Questions for Discussion 158 viii UNIT 11: Information and Knowledge Management Chapter 6: Medical Concept Representation 163 1 . Introduction 165 1.1 Use-cases 165 2 . Context 168 2.1 Concept Characteristics 169 2.2 Domains 170 2.3 Structure 171 3 . Biomedical Concept Collections 172 3.1 Ontologies 172 3.2 Vocabularies and Terminologies 174 3.3 Aggregation and Classification 175 3.4 Thesauri and Mappings 176 4 . Standards and Semantic Interoperability 177 5 . Acknowledgements 178 References 178 Suggested Readings 180 Online Resources 181 Questions for Discussion 181 Chapter 7: Characterizing Biomedical Concept Relationships: Concept Relationships as a Pathway for Knowledge Creation and Discovery 183 . 1 Introduction 185 2 . Background and Overview: The Use of Concept Relationships for Knowledge Creation 188 2.1 Indexing Strategies and Vocabulary Systems 190 2.2 Integrating Document Structure in Systems 192 2.3 Text Mining Approaches 194 2.4 Literature-based Discovery IR Systems 195 2.5 Summary 198 . 3 Case Examples 198 3.1 Genescene 199 3.2 Telemakus 200 3.3 How Can a Concept Relationship System Help with the Researcher's Problem and Questions? 202 3.4 Summary 206 4 . Conclusions and Discussion 206 5 . Acknowledgements 207 References 207 Suggested Readings 209 Online Resources 210 Questions for Discussion 210 Chapter 8: Biomedical Ontologies 211 1 . Introduction 213 2 . Representation of the Biomedical Domain in General Ontologies 215 2.1 OpenCyc 215 2.2 WordNet 215 3 . Examples of Medical Ontologies 217 3.1 GALEN 217 3.2 Unified Medical Language System 219 3.3 The Systematized Nomenclature of Medicine 220 3.4 Foundational Model of Anatomy 222 3.5 MENELAS ontology 223 4 . Representations of the Concept Blood 224 4.1 Blood in Biomedical Ontologies 225 4.2 Differing Representations 227 4.3 Additional Knowledge 229 5 . Issues in Aligning and Creating Biomedical Ontologies 230 6 . Conclusion 231 7 . Acknowledgments 232 References 232 Suggested Readings 234 Online Resources 234 Questions for Discussion 235 Appendix: Table showing characteristics of selected ontologies 235 Chapter 9: Information Retrieval and Digital Libraries 237 Overview of Fields 239 Information Retrieval 241 2.1 Content 242 2.2 Indexing 247 2.3 Retrieval 254 2.4 Evaluation 257 2.5 Research Directions 261 Digital Libraries 262 3.1 Access 262 3.2 Interoperability 263 3.3 Preservation 263 Case Studies 264 4.1 PubMed 264 4.2 User-oriented Evaluation 265 4.3 Changes in Publishing 267 Acknowledgements 269 References 269 Suggested Readings 273 Online Resources 274 Questions for Discussion 275 Chapter 10: Modeling Text Retrieval in Biomedicine 277 1 . Introduction 279 2 . Literature Review 280 3 . An Ideal Model 282 4 . General Text Retrieval 284 4.1 Vector Models 284 4.2 Language Models 286 5 . Example Text Retrieval Systems Specialized to a Biological Domain 288 5.1 Telemakus 289 5.2 XplorMed 290 5.3 AI3View:HivResist 291 5.4 The Future 292 [...]... major US corporations and been awarded numerous industry awards including: AT&T Foundation Award in Science and Engineering, SAP Award in ResearchlApplications, and Andersen Consulting Professor of the Year Award Dr Chen has been heavily involved in fostering digital library, medical informatics, knowledge management, and intelligence informatics research and education in the US and internationally Dr... l@health.state.ny.us) Zan Huang is a PhD candidate in Management Information Systems at the University of Arizona and is a research associate in the Artificial Intelligence Lab He earned his B.Eng in Management Information Systems from Tsinghua University His research interests include data mining in biomedical and business applications, recommender systems, and mapping knowledge domains (Eniail: zhuang@eller.arizona.edu... research interests are in text -mining and knowledge representation (Email: dingjing@iastate.edu) Pan Du received the BS and MS degrees in Electrical Engineering from National University of Defense Technology, Changsha, China, in 1995 and 1998, respectively He is currently a co-major PhD student in Electrical Engineering major and Bioinformatics and Computational Biology major at Department of Electrical and. .. tagging, information extraction and text data mining (Email: tanabe@ncbi.nlm.nih.gov) Peter Tarczy-Hornoch, MD, is an Associate Professor in the Department of Pediatrics and in the Department of Medical Education and Biomedical Informatics and an Adjunct Associate Professor in the Department of Computer Science and Engineering at the University of Washington Within the Department of Medical Education and. .. Telemakus: Mining and Mapping Research Findings to Promote Knowledge Discovery in Aging funded by the Ellison Medical Foundation; Co-Investigator of Biomedical Applications of the Next Generation Internet (NGI): Patientcentric Tools for Regional Collaborative Cancer Care Using the NGI funded by the National Library of Medicine; Co-Investigator of an International Health and Biomedical Research and Training... University Purdue University Indianapolis He received his Ph D in computer science from Concordia University, Montreal in 1987 His primary research interests are in pattern analysis and machine intelligence He is working on problems related to information management using information filtering and text mining approaches and structural health monitoring and smart diagnostics based on intelligent computational... Sciences and MS in Management Information Systems from the University of Arizona Her research interests lie in biomedical data mining, knowledge integration, and their applications in genomics (Email: hsu@eller arizona.edu; URL: http:Nai.eller.arizona.edu/people/hsu/) Lorraine Tanabe, PhD, holds a B.S in Molecular Biology from San Jose State University, and a PhD in Computational Sciences and Informatics. .. Division of General Internal Medicine of the Department of Medicine and in the Department of Public Health and Preventive Medicine Dr Hersh obtained his B.S in Biology from the University of Illinois at Champaign-Urbana in 1980 and his M.D from the University of Illinois at Chicago in 1984 After finishing his residency in Internal Medicine at University of Illinois Hospital in Chicago in 1987, he completed... Readings 590 Online Resources 590 Questionsfor Discussion 591 Chapter 21: Joint Learning Using Multiple Types of Data and Knowledge 593 1 2 3 4 Introduction 595 Overview of the Field 597 2.1 Large-scale Biological Data and Knowledge Resources .597 2.2 Joint Learning Using Multiple Types of Data 599 2.3 Joint Learning Using Data and. .. Professor in the Department of Computer and Information Science and Associate Director (Bioinformatics) in the School of Informatics at Indiana University Purdue University Indianapolis Dr Mukhopadhyay is a holder of degrees from Jadavpur University, India and the Indian Institute of Science, India as well as a Master of Science and Doctorate in Electrical Engineering from Yale University His research interests . Management, Data Mining, and Text Mining Applications in Biomedicine 12 3.1 Ontologies 13 3.2 Knowledge Management 14 3.3 Data Mining and Text Mining. Topics in Medical In formatics Chapter 1: Knowledge Management. Data Mining. and Text Mining in Medical Informatics 3 Introduction 5 Knowledge Management,