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1 - 10 of 36 results for: BIOMEDIN

BIOMEDIN 156: Economics of Health and Medical Care (BIOMEDIN 256, ECON 126, HRP 256)

Institutional, theoretical, and empirical analysis of the problems of health and medical care. Topics: demand for medical care and medical insurance; institutions in the health sector; economics of information applied to the market for health insurance and for health care; measurement and valuation of health; competition in health care delivery. Graduate students with research interests should take ECON 249. Prerequisites: ECON 50 and either ECON 102A or STATS 116 or the equivalent. Recommended: ECON 51.
Terms: Aut | Units: 5 | UG Reqs: WAY-SI | Grading: Medical Option (Med-Ltr-CR/NC)

BIOMEDIN 200: Biomedical Informatics Colloquium

Series of colloquia offered by program faculty, students, and occasional guest lecturers. May be repeated three times for credit.
Terms: not given this year | Units: 1 | Repeatable for credit | Grading: Medical Satisfactory/No Credit

BIOMEDIN 201: Biomedical Informatics Student Seminar

Participants report on recent articles from the Biomedical Informatics literature or their research projects. Goals are to teach critical reading of scientific papers and presentation skills. May be repeated three times for credit.
Terms: Aut, Win, Spr, Sum | Units: 1 | Repeatable for credit | Grading: Medical Satisfactory/No Credit
Instructors: Musen, M. (PI)

BIOMEDIN 205: Precision Practice with Big Data

Primarily for M.D. students; open to other graduate students. Provides an overview of how to leverage large amounts of clinical, molecular, and imaging data within hospitals and in cyberspace--big data--to practice medicine more effectively. Lectures by physicians, researchers, and industry leaders survey how the major methods of informatics can help physicians leverage big data to profile disease, to personalize treatment to patients, to predict treatment response, to discover new knowledge, and to challenge established medical dogma and the current paradigm of clinical decision-making based solely on published knowledge and individual physician experience. May be repeated for credit. Prerequisite: background in biomedicine. Background in computer science can be helpful but not required.
Terms: Aut | Units: 1 | Repeatable for credit | Grading: Medical Satisfactory/No Credit

BIOMEDIN 206: Informatics in Industry

Effective management, modeling, acquisition, and mining of biomedical information in healthcare and biotechnology companies and approaches to information management adopted by companies in this ecosystem. Guest speakers from pharmaceutical/biotechnology companies, clinics/hospitals, health communities/portals, instrumentation/software vendors. May be repeated for credit.
Terms: Spr | Units: 1 | Repeatable for credit | Grading: Medical Satisfactory/No Credit
Instructors: Shah, N. (PI)

BIOMEDIN 207: Digital Medicine: How health IT is changing the practice of medicine

The widespread use of health IT, such as electronic health records, and of health applications by patients, will radically alter the practice of medicine in the coming decades. This seminar, comprised of guest lectures from industry and academia, will highlight the practical challenges and successes of how health IT has transformed care delivery programs. The seminar will cover current efforts in clinical decision support, patient-centered design, integration with community care, Big Data, and the innovation pipeline for healthcare delivery organizations.
Terms: Sum | Units: 1 | Grading: Medical Satisfactory/No Credit
Instructors: Cain, C. (PI)

BIOMEDIN 208: Clinical Informatics Literature Review Seminar

Focus is on reading and discussing seminal papers in clinical and health informatics. Topics include biomedical informatics methods, systems design, implementation and evaluation. Limited enrollment.
Terms: Win | Units: 1 | Grading: Medical Satisfactory/No Credit

BIOMEDIN 210: Modeling Biomedical Systems: Ontology, Terminology, Problem Solving (CS 270)

Methods for modeling biomedical systems and for making those models explicit in the context of building software systems. Emphasis is on intelligent systems for decision support and Semantic Web applications. Topics: knowledge representation, controlled terminologies, ontologies, reusable problem solvers, and knowledge acquisition. Recommended: exposure to object-oriented systems, basic biology.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

BIOMEDIN 212: Introduction to Biomedical Informatics Research Methodology (BIOE 212, CS 272, GENE 212)

Capstone Biomedical Informatics (BMI) experience. Hands-on software building. Student teams conceive, design, specify, implement, evaluate, and report on a software project in the domain of biomedicine. Creating written proposals, peer review, providing status reports, and preparing final reports. Issues related to research reproducibility. Guest lectures from professional biomedical informatics systems builders on issues related to the process of project management. Software engineering basics. Because the team projects start in the first week of class, attendance that week is strongly recommended. Prerequisites: BIOMEDIN 210 or 211 or 214 or 217. or consent of instructor. Preference to BMI graduate students. Consent of instructor required.
Terms: Spr | Units: 3-5 | Grading: Medical Option (Med-Ltr-CR/NC)
Instructors: Altman, R. (PI)

BIOMEDIN 214: Representations and Algorithms for Computational Molecular Biology (BIOE 214, CS 274, GENE 214)

Topics: introduction to bioinformatics and computational biology, algorithms for alignment of biological sequences and structures, computing with strings, phylogenetic tree construction, hidden Markov models, Gibbs Sampling, basic structural computations on proteins, protein structure prediction, protein threading techniques, homology modeling, molecular dynamics and energy minimization, statistical analysis of 3D biological data, integration of data sources, knowledge representation and controlled terminologies for molecular biology, microarray analysis, machine learning (clustering and classification), and natural language text processing. Prerequisites: programming skills; consent of instructor for 3 units.
Terms: Aut | Units: 3-4 | Grading: Medical Option (Med-Ltr-CR/NC)
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