NSU HPD Catalog 2021-2022

108 Dr. Kiran C. Patel College of Osteopathic Medicine—Health Informatics Program infrastructures for the accurate and efficient analysis of big data for health care applications. Students will learn the mathematical, statistical, artificial intelligence, and modeling techniques that have been developed for analysis of big data, especially for health care applications. Also, it will describe the visualization techniques that are useful for displaying big data analysis results for meaningful interpretation of the results by humans. It will use current, real-world problems involving big data analytics in health care, including the Big Data to Knowledge (BD2K) initiative of the National Institutes of Health. Students will gain experience in applying the techniques of big data analytics to health care problems. (3 credit hours) MI 6700—Computational Informatics This course will provide an introductory, hands-on experience for life science researchers in bioinformatics using R and Bioconductor. Emphasis will be placed on accessing, formatting, and visualizing genomics data. Most analyses will deal with “little” data (nomapping or assembly of short reads), but some techniques to work with “big” data (e.g., BAM files) will be covered. Lecture and lab will both be held in a computer lab, so lecture will be hands-on. Working in small groups is encouraged. (3 credit hours) MI 6900—Bioinformatics This course introduces the concepts and practice of bioinformatics. Topics of discussion include biological databases, sequence alignment, gene and protein structure prediction, molecular phylogenetics, genomics, and proteomics. This is a hands-on, skill-based class. Students will develop basic skills in the collection and presentation of bioinformatics data, as well as the rudiments of programming in a scripting language. (3 credit hours) MI 7000—Health Informatics Project/Practicum This is a required course for all M.S. students. The practicum allows the student to select an area of interest in which to apply the theories, concepts, knowledge, and skills gained during the didactic courses in a real-world setting. The student will work under the supervision of a site-based preceptor and an NSU-based faculty adviser. The student is expected to acquire skills and experiences in the application of basic health informatics concepts and specialty knowledge to the solution of health information technology (HIT) problems. Students will be actively involved in the development, implementation, or evaluation of an informaticsbased application or project. A specific set of measurable learning objectives and deliverables will be determined by the student, the site preceptor, and the NSU-based faculty adviser. These learning objectives must be approved by the course director. The student’s area of interest would be determined at an earlier point in the program or by the needs of the precepting organization. The practicum is evaluated by completion of an ePortfolio. The ePortfolio is an evidence-based digital format method used by the program to assess the quality and quantity of learning gained from a student practicum experience. The ePortfolio is standardized in its structure and format, yet individualized in its content for each student. Overall, the ePortfolio is goaldriven documentation of professional growth and achieved competencies during the practicum. The ePortfolio combines self-reflection, instructor assessments, and documentation supplied by students (evidence/samples) to document what they learned/produced. It is used to help students prepare for career transition/development. (4 credit hours) Students are responsible for finding their own practicum site. Once a site is located, the program office will facilitate a legal affiliation agreement between the site and the program. Some practicum sites may require background checks, drug screening, and immunization records. Students are responsible for any associated costs. MI 8000—Health Informatics Continuing Services This is an individualized course. (1 credit hour) PUH 5301—Biostatistics This course focuses on the principles and reasoning underlying modern biostatistics and on specific inferential techniques commonly used in public health research. At course completion, students will be able to apply basic inferential methods in research endeavors and improve their abilities to understand the data analysis of health-related research articles. (3 credit hours) PUH 5430—Epidemiology This course examines basic principles and methods of modern epidemiology used to assess disease causation and distribution. Students develop conceptual and analytical skills to measure association and risk, conduct epidemiological surveillance, evaluate screening and diagnostic tests, and investigate disease outbreaks and epidemics. (3 credit hours) Health Informatics Program Department Director and Associate Professor: S. Bronsburg | Professors: P. Hardigan, R. Jacobs, R. Ownby | Associate Professor: S. Craddock | Assistant Professor: G. Cravens | Adjunct Associate Professors: K. Clauson, D. Hays, M. Shen, J. Singer | Adjunct Assistant Professors: R. AlHazme, P. Casimir, D. Dittman, J. Krive, E. Popovich, M. Ramim, D. Segura, J. Templeton, H. Wiggin | Adjunct Instructors: J. Garcia, D. Patrishkoff

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