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

xi

References ........................................................................................................... 294

Suggested Readings ................................................................................................ 295

Online Resources .................................................................................................... 296

Questions for Discussion ........................................................................................ 296

Chapter 11: Public Access to Anatomic Images ................................... 299

Introduction .................................................................................................... 301

Background .................................................................................................... 303

2.1 Previous Work ....................................................................................... 303

2.2 Prologue: Database Design .................................................................. 305

The AnatQuest System .................................................................................. 308

3.1 Need for Public Access ......................................................................... 308

3.2 AnatQuest: Design Considerations ....................................................... 309

3.3 AnatQuest for Onsite Visitors ............................................................... 315

Next Steps .................................................................................................. 16

4.1 Increasing Content ............................................................................ 316

4.2 Linking Text Resources to Image Database ........................................ 18

4.3 Implemented Prototype: MedlinePlus Proxy Server ............................ 328

Summary ........................................................................................................ 330

Acknowledgements ........................................................................................ 330

References ............................................................................................................... 330

Suggested Readings ................................................................................................ 331

Online Resources ................................................................................................. 332

Questions for Discussion ........................................................................................ 332

Chapter 12: 3D Medical Informatics: Information Science

in Multiple Dimensions ....................................................................... 333

Introduction .................................................................................................... 335

Overview . 3D Medical Informatics ............................................................. 337

2.1 From Data to Knowledge ...................................................................... 339

2.2 History ................................................................................................... 340

2.3 Why Study 3D Medical Informatics? .................................................... 342

Example: 3D Models and Measurement of Neuroanatomy

across Subjects ............................................................................................... 344

3.1 Indexing Images with 3D Medical Informatics ..................................... 345

3.2 Generalizing Elastic Deformable Models to 3D .................................... 346

xii

4 . Surgical Templates: A Case Study in 3D Informatics .................................. 348

4.1 Background and Related work .............................................................. 348

4.2 Design and Software Tools for Template Planning

Workstation .................................................................................................... 349

4.3 Results and Discussion .......................................................................... 350

5 . Grand Challenges in 3D Medical Informatics ............................................... 353

6 . Conclusion .................................................................................................... 354

7 . Acknowledgements ........................................................................................ 355

References .............................................................................................................. 355

Suggested Readings ................................................................................................ 356

Online Resources ................................................................................................ 357

Questions for Discussion ........................................................................................ 357

Chapter 13: Infectious Disease Informatics and

Outbreak Detection .................................................................................. 359

Introduction .................................................................................................... 361

Infectious Disease Informatics: Background and Overview ......................... 362

2.1 Practical Challenges and Research Issues ............................................. 362

2.2 Infectious Disease Informatics Research Framework ........................... 365

2.3 Infectious Disease Information Sharing Infrastructure .......................... 367

2.4 Infectious Disease Data Analysis and Outbreak

Detection ............................................................................................... 372

Infectious Disease Information Infrastructure and Outbreak

Detection: Case Studies ............................................................................... 378

3.1 New York State's Health Information Network System ....................... 378

3.2 The BioPortal System ............................................................................ 379

3.3 West Nile Virus Outbreak Analysis ............................... .... .............. 386

Conclusions and Discussion .......................................................................... 388

Acknowledgements ...................................................................................... 391

References ....................... ................................... ......................................... 391

Suggested Readings ................................................................................................ 394

Online Resources ........................... ................................................................. 394

Questions for Discussion ........................................................................................ 394

xiii

UNIT 111: Text Mining and Data Mining

Chapter 14: Semantic Interpretation for the Biomedical

Research Literature ................................................................................. 399

Introduction ............... .............................................................................. 401

Natural Language Processing ......................................................................... 401

2.1 Overview ............................................................................................... 401

2.2 Levels of Linguistic Structure ............................................................... 402

Domain Knowledge: The UMLS ................................................................... 403

3.1 SPECIALIST Lexicon ........................................................................... 404

3.2 Metathesaurus ..................................................................................... 404

Semantic Network .......................................................................................... 405

Semantic Interpretation for the Biomedical Literature ................................... 406

4.1 Overview ............................................................................................... 406

4.2 AQUA ................................................................................................... 407

4.3 PROTEUS-BIO ..................................................................................... 408

4.4 SemRep ................................................................................................. 409

4.5 Comparison of AQUA, PROTEUS-BIO, and SemRep ......................... 414

Application of SemRep .................................................................................. 414

5.1 Automatic Summarization ..................................................................... 414

5.2 lnformation Extraction in Molecular Genetics ...................................... 417

Conclusion .................................................................................................... 419

References ............... ................................................................................... 420

Suggested Readings ................................................................................................ 421

Online Resources .................................................................................................... 422

Questions for Discussion ........................................................................................ 422

Chapter 15: Semantic Text Parsing for Patient Records .................... 423

1 . Introduction ......... ....................................................................................... 425

2 . Overview ........................................................................................................ 427

2.1 Challenges of Processing Clinical Reports ............................................ 427

2.2 Components of an NLP System ............................................................ 431

2.3 Clinical Applications ............................................................................. 437

3 . Case Scenario ................................................................................................. 439

4 . Conclusions and Discussion ........................................................................... 443

5 . Acknowledgements ........................................................................................ 443

xiv

References ............................................................................................................... 444

Suggested Readings .............................................................................................. 446

Online Resources .................................................................................................. 447

Questions for Discussion ........................................................................................ 447

Chapter 16: Identification of Biological Relationships

from Text Documents .............................................................................. 449

Introduction .................................................................................................... 451

Overview of the Field .................................................................................... 453

2.1 Background ........................................................................................... 453

2.2 Biological Information Extraction ......................................................... 453

2.3 Bioinformatics Tools ............................................................................. 456

Case Studies ................................................................................................... 457

3.1 Identification of Flat Relationships from Text Documents ................... 457

3.2 TransMiner: Formulating Novel, Implicit Associations

through Transitive Closure .................................................................... 461

3.3 Identification of Directional and Hierarchical Relationships 466 ................

BioMap: A Knowledge Base of Biological Literature ................................... 477

4.1 BioMap Knowledgebase ....................................................................... 480

4.2 Results and Discussions ........................................................................ 482

Conclusions .................................................................................................... 484

Acknowledgements ........................................................................................ 484

References ............. ............................................................................................ 48.5

Suggested Readings ................................................................................................ 487

Online Resources .................................................................................................... 488

Questions for Discussion ........................................................................................ 488

Chapter 17: Creating. Modeling and Visualizing Metabolic

Networks: FCModeler and PathBinder for Network

Modeling and Creation ....................................................................... 491

1 . Introduction .......... .................................................................................... 493

2 . Overview ........................................................................................................ 494

2.1 Metabolic Pathway Databases ............................................................... 494

2.2 Network Modeling and Reconstruction ................................................. 494

2.3 Extracting Biological Interactions from Text ........................................ 495

3 . Metnet ............................................................................................................ 498

3.1 Metabolic Networking Data Base (MetNetDB) .................................... 498

3.2 FCModeler: Network Visualization and Modeling ............................... 499

3.3 Network Validation Using Fuzzy Metrics ............................................. 502

3.4 PathBinderA: Finding Sentences with Biomolecular ........................... 504

Interactions ........................................................................................... SO4

4 . Building on Metabolic Networks: Using MetNet .......................................... 508

4.1 Construct the Genetic Network Using Time Correlation ...................... 508

4.2 Cluster and Network Validation ............................................................ 509

5 . Discussion .................................................................................................... 514

6 . Acknowledgements ........................................................................................ 514

References ............................................................................................................... 515

Suggested Readings ............................................................................................... 7

Online Resources ................................ ................................................................ 7

Questions for Discussion ........................................................................................ 518

Chapter 18: Gene Pathway Text Mining and Visualization ................ 519

1 . Introduction .................................................................................................... 521

2 . Literature Review/Overview ......................................................................... S21

2.1 Text Mining .......................................................................................... S21

2.2 Visualization ......................................................................................... 525

3 . Case Studies/Examples .................................................................................. 526

3.1 Arizona Relation Parser ........................................................................ 527

3.2 Genescene Parser .................................................................................. 534

3.3 Genescene Visualizer ........................................................................... 538

4 . Conclusions and Discussion ........................................................................... 541

5 . Acknowledgements ........................................................................................ 542

References ............................................................................................................... 542

Suggested Readings ................................................................................................ 544

Online Resources .................................................................................................... 545

Questions for Discussion ...................................................................................... 545

Chapter 19: The Genomic Data Mine ................................................... 547

1 . Introduction .................................................................................................... 549

2 . Overview ........................................................................................................ 550

2.1 Genomic Text Data ............................................................................... 551

2.2 Genomic Map Data ............................................................................... 556