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

Jules J. Berman

ISBN 10: 1439841829 / ISBN 13: 9781439841822

Verlag: Chapman and Hall/CRC 2015-02-04, 2015

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Bestandsnummer des Verkäufers 6666-TNFPD-9781439841822

Bibliografische Details

Titel: Methods in Medical Informatics: Fundamentals...

Verlag: Chapman and Hall/CRC 2015-02-04

Erscheinungsdatum: 2015

Einband: Hardcover

Zustand: New

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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