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Methods in Medical Informatics: Fundamentals of Healthcare Programming in Perl, Python, and Ruby (Chapman & Hall/CRC Mathematical & Computational Biology)
 
 

Methods in Medical Informatics: Fundamentals of Healthcare Programming in Perl, Python, and Ruby (Chapman & Hall/CRC Mathematical & Computational Biology) [Print Replica] [Kindle Edition]

Jules J. Berman

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Review

As subspecialty board certification in clinical informatics has finally become a reality, Jules Berman’s Methods in Medical Informatics could not be more timely. This well-written and informative text combines Dr. Berman’s expertise in programming with his vast knowledge of publicly available data sets and everyday healthcare programming needs to result in a book which … should become a staple in health informatics education programs as well as a standard addition to the personal libraries of informaticists.
—Alexis B. Carter, Journal of Pathology Informatics, October 2011

This book provides an introduction to processing clinical and population health data using rigorous methods and widely available, low cost, but very capable tools. The inclusion of the three leading dynamic programming languages broadens the appeal … bridges the gap from programming instruction to dealing with specialized medical data, making it possible to teach a relevant programming course in a biomedical environment. I would have loved to have a copy of this when I was teaching introductory programming for medical informatics.
—Professor James H. Harrison, Jr., Director of Clinical Informatics, University of Virginia

… presents students and professionals in the healthcare field (who have some working knowledge of the open-source programming languages Perl, Python, or Ruby) with instruction for applying basic informatics algorithms to medical data sets. He [the author] provides algorithm scripts for each of the languages, along with step-by-step explanations of the algorithms used for retrieving, organizing, merging, and analyzing such data sources as the National Cancer Institute’s Surveillance Epidemiology and End Results project, the National Library of Medicine’s PubMed service, the mortality records of the US Centers for Disease Control and Prevention, the US Census, and the Online Mendelian Inheritance in Man data set on inherited conditions.
SciTech Book News, February 2011

Product Description

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.

Product details

  • Format: Kindle Edition
  • File Size: 9147 KB
  • Print Length: 413 pages
  • Publisher: Chapman and Hall/CRC; 1 edition (22 Aug 2012)
  • Sold by: Amazon Media EU S.à r.l.
  • Language: English
  • ASIN: B00918NF8Q
  • Text-to-Speech: Not enabled
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  • Amazon Bestsellers Rank: #840,775 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Amazon.com: 4.4 out of 5 stars  5 reviews
2.0 out of 5 stars Lots of errors in code and reference link are out of date! 2 July 2013
By S. MOK - Published on Amazon.com
Format:Hardcover|Verified Purchase
Lots of errors in code and reference link are out of date! You should be prepared to fix a lot of little errors in the provided code.
5.0 out of 5 stars A Must for Anyone Interested in Clinical Informatics 10 Oct 2011
By Alexis B. Carter - Published on Amazon.com
Format:Hardcover
This review can also be found in the Journal of Pathology Informatics ([...]), an open access journal for the field of Pathology Informatics.

As subspecialty board certification in clinical informatics has finally become a reality, Jules Berman's book Methods in Medical Informatics could not be more timely. This well-written and informative text combines Dr. Berman's expertise in programming with his vast knowledge of publicly available data sets and everyday healthcare programming needs to result in a book which should, in the opinion of this reviewer, become a staple in health informatics education programs as well as a standard addition to the personal libraries of informaticists.

The book's title does not do justice to the wealth of information contained therein. While Python, Perl, and Ruby are certainly important components of the text as described below, the contents also house a huge amount of valuable information on publicly available data sets and how they can be accessed and used for medical discovery. Through parallel examples in Python, Perl, and Ruby, the reader is taken through sets of structured exercises, each of which includes a description of the problem or task, a human readable explanation of the script algorithm, script examples and analysis of the expected results. While this book was not intended for the novice programmer, the organization and structure of its content and explanation of the process behind the code easily facilitate a reader's ability to use the examples on his or her own computer with a minimum of background in each of the languages provided.

During the process of reviewing this book, the reviewer (who had never previously used any of these programming languages and who is a relative novice to code-writing) used the author's instructions to install the Python compiler. After some additional background reading in Python and its code construct from another source, several of the exercises in the book were tested using Python as the language of choice. As expected in any book containing programming code, versions of the programming languages used when writing a book are sometimes not the most recent stable version available for download by the reader at a later date. This appears to be more of an issue with open source programming languages because they are updated more frequently. The stable versions of Python available for download at the time of review were 2.7.2 and 3.2.2 (Perl is on version 5.14.2; Ruby is on version 1.9.2). The version of Python used in the book is 2.5 (Perl 5.8; Ruby 1.8). An example of a difference between these two versions of Python is a slightly change to the syntax for print statements, which led to some initial stalls in getting the examples to run correctly. However, this was a minor setback which was easily overcome and did not detract from rest of the book.

The book is split into four major parts and is supplemented by an epilogue and appendices. Part I on fundamental methods and algorithms covers basic computing functions such as string and image manipulation, including hash creation and text indexing. Part II on medical data resources walks the reader through a vast array of useful and publicly available data resources for research and discovery. These include but are not limited to the National Library of Medicine's Medical Subject Headings (MeSH), the Cancer Surveillance Epidemiology and End Results (SEER) Program, Online Mendelian Inheritance in Man (OMIM), PubMed, United States census files, Centers for Disease Control and Prevention (CDC) data sets and others. The reader is also introduced into an author-developed taxonomy of neoplasms. In Part III on primary tasks (i.e. fundamental scripts) for medical informatics, basic concept-indexing, scrubbing of patient identifiers from text reports, web page construction and common gateway interfaces are demonstrated as well as image annotation and use of extensible markup language (XML) and resource description framework (RDF) files. Part IV on medical discovery uses case studies to illustrate how these powerful programming techniques can enable researchers to discover information from publicly available data sets. Examples include extracting emphysema rates from CDC data, cancer epidemiological data from the SEER database and others.

The epilogue offers sage advice on how to successfully get involved in programming and informatics as a career, and the appendices have complete instructions on how to acquire all of the programming applications used in the book as well as publicly available data sets. Additional information on other publicly available files, data sets and utilities that were not covered in the examples are also included.

In conclusion, this book is for anyone who wants to learn more about medical informatics. The book contains beautifully simple examples of how to use publicly available programming languages to get a job done, and in addition opens the door to a host of incredibly useful data sets to many who may not have been aware of their existence. Both medical professionals with only peripheral knowledge of programming and nonmedical information technology professionals will find this book useful, and its structure is ideal for biomedical informatics classrooms and clinical informatics fellowships alike.

Alexis Carter, MD
Director of Pathology Informatics
Emory University
Atlanta, GA
5.0 out of 5 stars Excellent resource for any healthcare worker with a special interest in Medical Informatics. 6 Mar 2011
By icc - Published on Amazon.com
Format:Hardcover
The book is addressed to healthcare workers (students, physicians or researchers) who have basic programming skills, and are interested to use these skills to help their patients, or to advance the medical science. The author includes in this work fundamental algorithms and methods of medical informatics with application to medical data sets, as well as step-by-step instruction and concrete examples. The script examples provided work both on Windows based PCs and on Macs and are excellent resources even for beginners who are not very familiarized with any of the three programming languages (Perl, Phyton or Ruby).
In addition, this book provides references to excellent public medical data resources, covers some of the computational methods of biomedical informatics, including autocoding, data scrubbing and data deidentification. The author also included examples of questions that biomedical scientists can address, in relation to medical data and open source programming language. He maintains a Website with updated resources related to all his published books.
In the context of a new era of medicine with widespread implementation of electronic medical records and electronic health records, this textbook is an invaluable resource.
5.0 out of 5 stars A very useful and practical book 6 Mar 2011
By Y Qian - Published on Amazon.com
Format:Hardcover
By using public data such as MeSH, ICD, OMIM, U.S. Census Files, etc, the author lists numerous small scripts to solve common Biomedical Informatics problems. Each script is explained by step-to-step script algorithm. Any Medical Informatician, even with limited programming skills, can easily understand the book contents and may apply the knowledge to solve similar problems in Biomedical domain. By avoiding language specific tricks, the book is especially useful for those who aren't familiar with or just heard of Perl, Python, and Ruby, but really want to try it out for potential use in their own Informatics practice.
5.0 out of 5 stars an accessible introduction for data analysts and students 9 Dec 2010
By L. Han - Published on Amazon.com
Format:Hardcover
"This book provides an introduction to processing clinical and population health data using rigorous methods and widely available, low cost, but very capable tools. The inclusion of the three leading dynamic programming languages broadens the appeal... bridges the gap from programming instruction to dealing with specialized medical data, making it possible to teach a relevant programming course in a biomedical environment. I would have loved to have a copy of this when I was teaching introductory programming for medical informatics." -Professor James H. Harrison, Jr., Director of Clinical Informatics, University of Virginia
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