Methods in Biomedical Informatics

  • ID: 2485197
  • Book
  • 592 Pages
  • Elsevier Science and Technology
1 of 4

Beginning with a survey of fundamental concepts associated with data integration, knowledge representation, and hypothesis generation from heterogeneous data sets, Methods in Biomedical Informatics provides a practical survey of methodologies used in biological, clinical, and public health contexts. These concepts provide the foundation for more advanced topics like information retrieval, natural language processing, Bayesian modeling, and learning classifier systems. The survey of topics then concludes with an exposition of essential methods associated with engineering, personalized medicine, and linking of genomic and clinical data. Within an overall context of the scientific method, Methods in Biomedical Informatics provides a practical coverage of topics that is specifically designed for: (1) domain experts seeking an understanding of biomedical informatics approaches for addressing specific methodological needs; or (2) biomedical informaticians seeking an approachable overview of methodologies that can be used in scenarios germane to biomedical research.

  • Contributors represent leading biomedical informatics experts: individuals who have demonstrated effective use of biomedical informatics methodologies in the real-world, high-quality biomedical applications
  • Material is presented as a balance between foundational coverage of core topics in biomedical informatics with practical "in-the-trenches" scenarios.
  • Contains appendices that function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4) Web Services.
Note: Product cover images may vary from those shown
2 of 4

1. Introduction
Indra Neil Sarkar 2. Data Integration: An Overview
Prakash Nadkarni and Luis Marenco 3. Knowledge Representation
Mark A. Musen 4. Hypothesis Generation from Heterogenous Data Sets
Yves A. Lussier and Haiquan Li 5. Geometric Representations in Biomedical Informatics: Applications in Automated Text Analysis
Trevor Cohen and Dominic Widdows 6. Biomedical Natural Language Processing and Text Mining
Kevin B. Cohen 7. Knowledge Discovery in Biomedical Data: Theory and Methods
John H. Holmes 8. Bayesian Methods in Biomedical Data Analysis
Hsun-Hsien Chang and Gil Alterovitz 9. Learning Classifier Systems: The Rise of Genetics-Based Machine Learning in Biomedical Data Mining
Ryan J. Urbanowicz and Jason H. Moore 10. Engineering Principles in Biomedical Informatics
Riccardo Bellazzi, Matteo Gabetta, Giorgio Leonardi 11. Biomedical Informatics Methods for Personalized Medicine and Participatory Health
Fernando Martin-Sanchez, Guillermo Lopez-Campos, Kathleen Gray 12. Linking Genomic and Clinical Data for Discovery and Personalized Care
Joshua C. Denny and Hua Xu 13. Putting Theory into Practice
Indra Neil Sarkar

Appendices A1: Unix Primer
Elizabeth S. Chen A2: Ruby Primer
Elizabeth S. Chen A3: Database Primer
Elizabeth S. Chen A4: Web Services
Elizabeth S. Chen

Note: Product cover images may vary from those shown
3 of 4

Loading
LOADING...

4 of 4
Sarkar, Indra Neil
Note: Product cover images may vary from those shown
5 of 4
Note: Product cover images may vary from those shown
Adroll
adroll