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.
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
