BMI Course Information
BMI 511 Decision Support and Evidence-Based Practice (3)
Instructor Information |
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Fall 2009 |
Course not offered |
Spring 2009 |
Course not offered |
Catalog Description
Biomedical decision making and the tools and techniques for decision support, including artificial intelligence and machine learning techniques.
Prerequisites
General BMI Admission Criteria
Textbook and Other Materials
The Guide to Clinical Preventive Services, 2006 (AHRQ Publication No. 06-0588).
Course Learning Outcomes
Students will understand the use of quantitative and qualitative tools for decision support and data analysis including:
- Clinical study design, study proposal development, and experimental design and statistics (includes sampling, survey design, and analysis and population and demographics data for clinical trials).
- Guideline development and application/evidence based medicine.
- Clinical decision making/application of quantitative and qualitative tools.
- Artificial intelligence techniques and machine learning for proteomic and demonic analysis (includes simulation, modeling of biological systems, mathematical modeling, and data clustering).
Major Topics and Time Covered
Quantitative and qualitative decision methods will be explored with biomedical applications. Artificial intelligence and machine learning techniques will also be applied to biomedical problems and decision support.
- Guideline development, maintenance and applications
- Guideline significance in health policy and clinical decision making
- Evidence based medicine principles including levels of evidence quality and study review
- Use of heuristic rules in biomedical decision making
- Quantitative decision support techniques including Bayesian analysis, simulation, population analysis
- Biological system modeling
- Markov and Monte Carlo modeling
- Artificial intelligence theory and biomedical applications