Berman Methods in Medical Informatics

Fundamentals of Healthcare Programming in Perl, Python, and Ruby
1. Auflage 2010
ISBN: 978-1-4398-4184-6
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: 0 - No protection

E-Book, Englisch, 413 Seiten

Reihe: Chapman & Hall/CRC Mathematical & Computational Biology

Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implemented with open source programming languages, you can fully utilize the medical information contained in clinical and research datasets. The common computational tasks of medical informatics are accessible to anyone willing to learn the basics.

Methods in Medical Informatics: Fundamentals of Healthcare Programming in Perl, Python, and Ruby demonstrates that biomedical professionals with fundamental programming knowledge can master any kind of data collection. Providing you with access to data, nomenclatures, and programming scripts and languages that are all free and publicly available, this book —

- Describes the structure of data sources used, with instructions for downloading

- Includes a clearly written explanation of each algorithm

- Offers equivalent scripts in Perl, Python, and Ruby, for each algorithm

- Shows how to write short, quickly learned scripts, using a minimal selection of commands

- Teaches basic informatics methods for retrieving, organizing, merging, and analyzing data sources

- Provides case studies that detail the kinds of questions that biomedical scientists can ask and answer with public data and an open source programming language

Requiring no more than a working knowledge of Perl, Python, or Ruby, Methods in Medical Informatics will have you writing powerful programs in just a few minutes. Within its chapters, you will find descriptions of the basic methods and implementations needed to complete many of the projects you will encounter in your biomedical career.

Zielgruppe

Biomedical researchers, healthcare informaticians, policy makers and regulators, and other professionals involved in healthcare.

Autoren/Hrsg.

Berman, Jules J.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Telemedizin, e-Health
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Naturwissenschaften Biowissenschaften Biowissenschaften

Inhaltsverzeichnis

PART I FUNDAMENTAL ALGORITHMS AND METHODS OF MEDICAL INFORMATICS
Chapter 1 Parsing and Transforming Text Files
Peeking into Large Files
Paging through Large Text Files
Extracting Lines that Match a Regular Expression
Changing Every File in a Subdirectory
Counting the Words in a File
Making a Word List with Occurrence Tally
Using Printf Formatting Style
Chapter 2 Utility Scripts
Random Numbers
Converting Non-ASCII to Base64 ASCII
Creating a Universally Unique Identifier
Splitting Text into Sentences
One-Way Hash on a Name
One-Way Hash on a File
A Prime Number Generator
Chapter 3 Viewing and Modifying Images
Viewing a JPEG Image
Converting between Image Formats
Batch Conversions
Drawing a Graph from List Data
Drawing an Image Mashup
Chapter 4 Indexing Text
ZIPF Distribution of a Text File
Preparing a Concordance
Extracting Phrases
Preparing an Index
Comparing Texts Using Similarity Scores

PART II MEDICAL DATA RESOURCES
Chapter 5 The National Library of Medicine’s Medical Subject Headings (MeSH )
Determining the Hierarchical Lineage for MeSH Terms
Creating a MeSH Database
Reading the MeSH Database
Creating an SQLite Database for MeSH
Reading the SQLite MeSH Database
Chapter 6 The International Classification of Diseases
Creating the ICD Dictionary
Building the ICD-O (Oncology) Dictionary
Chapter 7 SEER: The Cancer Surveillance, Epidemiology, and End Results Program
Parsing the SEER Data Files
Finding the Occurrences of All Cancers in the SEER Data Files
Finding the Age Distributions of the Cancers in the SEER Data Files
Chapter 8 OMIM: The Online Mendelian Inheritance in Man
Collecting the OMIM Entry Terms
Finding Inherited Cancer Conditions
Chapter 9 PubMed
Building a Large Text Corpus of Biomedical Information
Creating a List of Doublets from a PubMed Corpus
Downloading Gene Synonyms from PubMed
Downloading Protein Synonyms from PubMed
Chapter 10 Taxonomy
Finding a Taxonomic Hierarchy
Finding the Restricted Classes of Human Infectious Pathogens
Chapter 11 Developmental Lineage Classification and Taxonomyof Neoplasms
Building the Doublet Hash
Scanning the Literature for Candidate Terms
Adding Terms to the Neoplasm Classification
Determining the Lineage of Every Neoplasm Concept
Chapter 12 U.S. Census Files
Total Population of the United States
Stratified Distribution for the U.S. Census
Adjusting for Age
Chapter 13 Centers for Disease Control and Prevention Mortality Files
Death Certificate Data
Obtaining the CDC Data Files
How Death Certificates Are Represented in Data Records
Ranking, by Number of Occurrences, Every Condition in the CDC
Mortality Files

PART III PRIMARY TASKS OF MEDICAL INFORMATICS
Chapter 14 Autocoding
A Neoplasm Autocoder
Recoding
Chapter 15 Text Scrubber for Deidentifyin g Confidential Text
Chapter 16 Web Pages and CGI Scripts
Grabbing Web Pages
CGI Script for Searching the Neoplasm Classification
Chapter 17 Image Annotation
Inserting a Header Comment
Extracting the Header Comment in a JPEG Image File
Inserting IPTC Annotations
Extracting Comment, EXIF, and IPTC Annotations
Dealing with DICOM
Finding DICOM Images
DICOM-to-JPEG Conversion
Chapter 18 Describing Data with Data, Using XML
Parsing XML
Resource Description Framework (RDF)
Dublin Core Metadata
Insert an RDF Document into an Image File
Insert an Image File into an RDF Document
RDF Schema
Visualizing an RDF Schema with GraphViz
Obtaining GraphViz
Converting a Data Structure to GraphViz

PART IV MEDICAL DISCOVERY
Chapter 19 Case Study: Emphysema Rates
Chapter 20 Case Study: Cancer Occurrence Rates
Chapter 21 Case Study: Germ Cell Tumor Rates across Ethnicities
Chapter 22 Case Study: Ranking the Death-Certifying Process, by State
Chapter 23 Case Study: Data Mashups for Epidemics
Tally of Coccidioidomycosis Cases by State
Creating the Map Mashup
Chapter 24 Case Study: Sickle Cell Rates
Chapter 25 Case Study: Site-Specific Tumor Biology
Anatomic Origins of Mesotheliomas
Mesothelioma Records in the SEER Data Sets
Graphic Representation
Chapter 26 Case Study: Bimodal Tumors
Chapter 27 Case Study: The Age of Occurrence of Precancers
Epilogue for Healthcare Professionals and Medical Scientists
Learn One or More Open Source Programming Languages
Don’t Agonize Over Which Language You Should Choose
Learn Algorithms
Unless You Are a Professional Programmer, Relax and Enjoy Being a Newbie
Do Not Delegate Simple Programming Tasks to Others
Break Complex Tasks into Simple Methods and Algorithms
Write Fast Scripts
Concentrate on the Questions, Not the Answers

Appendix
How to Acquire Ruby
How to Acquire Perl
How to Acquire Python
How to Acquire RMagick
How to Acquire SQLite
How to Acquire the Public Data Files Used in This Book
Other Publicly Available Files, Data Sets, and Utilities

Über Autor(innen)

Jules Berman, Ph.D., M.D., received two bachelor of science degrees (mathematics and earth sciences) from MIT, a Ph.D. in pathology from Temple University, and an M.D. from the University of Miami School of Medicine. His postdoctoral research was conducted at the National Cancer Institute. His medical residence in pathology was completed at the George Washington University School of Medicine. He became board certified in anatomic pathology and in cytopathology, and served as the chief of Anatomic Pathology, Surgical Pathology and Cytopathology at the Veterans Administration (VA) Medical Center in Baltimore, Maryland.
While at the Baltimore VA, Dr. Berman held appointments at the University of Maryland Medical Center and at theJohns Hopkins Medical Institutions. In 1998, he became the program director for pathology informatics in the Cancer Diagnosis Program at the U.S. National Cancer Institute. In 2006, he became president of the Association for Pathology Informatics. Over the course of his career, he has written, as first author, more than 100 publications, including five books in the field of medical informatics. Today, Dr. Berman is a full-time freelance writer.