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11 - 20 of 23 results for: BIOMEDIN ; Currently searching spring courses. You can expand your search to include all quarters

BIOMEDIN 225: Data Driven Medicine

The widespread adoption of electronic health records (EHRs) has created a new source of big data namely, the record of routine clinical practice as a by-product of care. This class will teach you how to use EHRs and other patient data in conjunction with recent advances in artificial intelligence (AI) and evolving business models to improve healthcare. Upon completing this course, you should be able to: differentiate between and give examples of categories of care questions that AI can help answer, describe common healthcare data sources and their relative advantages, limitations, and biases in enabling care transformation, understand the challenges in using various kinds of clinical data to create fair algorithmic interventions, design an analysis of a clinical dataset, evaluate and criticize published research to separate hype from reality. Prerequisites: enrollment in the MCiM program. This course is designed to prepare you to pose and answer meaningful clinical questions using healthcare data as well as understand how AI can be brought into clinical use safely, ethically and cost-effectively.
Terms: Spr | Units: 3
Instructors: Shah, N. (PI)

BIOMEDIN 226: Digital Health Practicum in a Health Care Delivery System

Practical experience implementing clinical informatics solutions with a focus on digital health in one of the largest healthcare delivery systems in the United States. Individual meetings with senior clinical informatics leaders to discuss elements of successful projects. Implementation opportunities include supporting the use of electronic health records, engagement of patients and providers via a personal health record, use of informatics to support patient service centers, and improvement of patient access to clinical data. Consent of course instructors required at least one quarter prior to student enrollment in course.
Terms: Aut, Win, Spr | Units: 2-3

BIOMEDIN 251: Outcomes Analysis (HRP 252, MED 252)

This course introduces and develops methods for conducting empirical research that address clinical and policy questions that are not suitable for randomized trials. Conceptual and applied models of causal inference guide the design of empirical research. Econometric and statistical models are used to conduct health outcomes research which use large existing medical, survey, and other databases Problem sets emphasize hands-on data analysis and application of methods, including re-analyses of well-known studies. This is a project-based course designed for students pursuing research training. Prerequisites: one or more courses in probability, and statistics or biostatistics.
Terms: Spr | Units: 4
Instructors: Bendavid, E. (PI)

BIOMEDIN 256: Economics of Health and Medical Care (BIOMEDIN 156, 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; economics of health care labor markets and health care production; and economic epidemiology. 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: Spr | Units: 5

BIOMEDIN 260: Computational Methods for Biomedical Image Analysis and Interpretation (BMP 260, CS 235, RAD 260)

The latest biological and medical imaging modalities and their applications in research and medicine. Focus is on computational analytic and interpretive approaches to optimize extraction and use of biological and clinical imaging data for diagnostic and therapeutic translational medical applications. Topics include major image databases, fundamental methods in image processing and quantitative extraction of image features, structured recording of image information including semantic features and ontologies, indexing, search and content-based image retrieval. Case studies include linking image data to genomic, phenotypic and clinical data, developing representations of image phenotypes for use in medical decision support and research applications and the role that biomedical imaging informatics plays in new questions in biomedical science. Includes a project. Enrollment for 3 units requires instructor consent. Prerequisites: programming ability at the level of CS 106A, familiarity with statistics, basic biology. Knowledge of Matlab or Python highly recommended.
Terms: Spr | Units: 3-4

BIOMEDIN 290: Biomedical Informatics Teaching Methods

Hands-on training in biomedical informatics pedagogy. Practical experience in pedagogical approaches, variously including didactic, inquiry, project, team, case, field, and/or problem-based approaches. Students create course content, including lectures, exercises, and assessments, and evaluate learning activities and outcomes. Prerequisite: instructor consent.
Terms: Aut, Win, Spr, Sum | Units: 1-6 | Repeatable 2 times (up to 12 units total)
Instructors: Altman, R. (PI) ; Ashley, E. (PI) ; Bassik, M. (PI) ; Batzoglou, S. (PI) ; Bayati, M. (PI) ; Bejerano, G. (PI) ; Bhattacharya, J. (PI) ; Blish, C. (PI) ; Boahen, K. (PI) ; Brandeau, M. (PI) ; Bustamante, C. (PI) ; Butte, A. (PI) ; Chang, H. (PI) ; Cherry, J. (PI) ; Cohen, S. (PI) ; Covert, M. (PI) ; Curtis, C. (PI) ; Das, A. (PI) ; Das, R. (PI) ; Davis, R. (PI) ; Delp, S. (PI) ; Desai, M. (PI) ; Dill, D. (PI) ; Dumontier, M. (PI) ; Elias, J. (PI) ; Fagan, L. (PI) ; Feldman, M. (PI) ; Ferrell, J. (PI) ; Fraser, H. (PI) ; Gerritsen, M. (PI) ; Gevaert, O. (PI) ; Goldstein, M. (PI) ; Greenleaf, W. (PI) ; Guibas, L. (PI) ; Hastie, T. (PI) ; Hlatky, M. (PI) ; Holmes, S. (PI) ; Ji, H. (PI) ; Karp, P. (PI) ; Khatri, P. (PI) ; Kim, S. (PI) ; Kirkegaard, K. (PI) ; Klein, T. (PI) ; Koller, D. (PI) ; Krummel, T. (PI) ; Kundaje, A. (PI) ; Levitt, M. (PI) ; Levitt, R. (PI) ; Li, J. (PI) ; Longhurst, C. (PI) ; Lowe, H. (PI) ; Mallick, P. (PI) ; Manning, C. (PI) ; McAdams, H. (PI) ; Menon, V. (PI) ; Montgomery, S. (PI) ; Musen, M. (PI) ; Napel, S. (PI) ; Nolan, G. (PI) ; Olshen, R. (PI) ; Owen, A. (PI) ; Owens, D. (PI) ; Paik, D. (PI) ; Palacios, J. (PI) ; Pande, V. (PI) ; Petrov, D. (PI) ; Plevritis, S. (PI) ; Poldrack, R. (PI) ; Pritchard, J. (PI) ; Relman, D. (PI) ; Rivas, M. (PI) ; Rubin, D. (PI) ; Sabatti, C. (PI) ; Salzman, J. (PI) ; Shachter, R. (PI) ; Shafer, R. (PI) ; Shah, N. (PI) ; Sherlock, G. (PI) ; Sidow, A. (PI) ; Snyder, M. (PI) ; Tang, H. (PI) ; Taylor, C. (PI) ; Tibshirani, R. (PI) ; Utz, P. (PI) ; Walker, M. (PI) ; Wall, D. (PI) ; Winograd, T. (PI) ; Wong, W. (PI) ; Xing, L. (PI) ; Zou, J. (PI)

BIOMEDIN 299: Directed Reading and Research

For students wishing to receive credit for directed reading or research time. Prerequisite: consent of instructor. (Staff)
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit
Instructors: Aghaeepour, N. (PI) ; Alarid Escudero, F. (PI) ; Altman, R. (PI) ; Ashley, E. (PI) ; Baiocchi, M. (PI) ; Bassik, M. (PI) ; Batzoglou, S. (PI) ; Bayati, M. (PI) ; Bejerano, G. (PI) ; Bendavid, E. (PI) ; Bhattacharya, J. (PI) ; Blish, C. (PI) ; Boahen, K. (PI) ; Brandeau, M. (PI) ; Bustamante, C. (PI) ; Butte, A. (PI) ; Chang, H. (PI) ; Chaudhari, A. (PI) ; Chen, J. (PI) ; Cherry, J. (PI) ; Cohen, S. (PI) ; Covert, M. (PI) ; Das, A. (PI) ; Das, R. (PI) ; Davis, R. (PI) ; Delp, S. (PI) ; Desai, M. (PI) ; Dill, D. (PI) ; Dror, R. (PI) ; Dumontier, M. (PI) ; Elias, J. (PI) ; Engelhardt, B. (PI) ; Fagan, L. (PI) ; Feldman, M. (PI) ; Ferrell, J. (PI) ; Fraser, H. (PI) ; Gentles, A. (PI) ; Gerritsen, M. (PI) ; Gevaert, O. (PI) ; Goldstein, M. (PI) ; Greenleaf, W. (PI) ; Guibas, L. (PI) ; Hastie, T. (PI) ; Hernandez-Boussard, T. (PI) ; Hlatky, M. (PI) ; Holmes, S. (PI) ; Jerby, L. (PI) ; Ji, H. (PI) ; Karp, P. (PI) ; Khatri, P. (PI) ; Kim, S. (PI) ; Kirkegaard, K. (PI) ; Klein, T. (PI) ; Koller, D. (PI) ; Krummel, T. (PI) ; Kundaje, A. (PI) ; Langlotz, C. (PI) ; Leskovec, J. (PI) ; Levitt, M. (PI) ; Li, J. (PI) ; Longhurst, C. (PI) ; Lowe, H. (PI) ; Lu, Y. (PI) ; Mallick, P. (PI) ; Manning, C. (PI) ; McAdams, H. (PI) ; Menon, V. (PI) ; Montgomery, S. (PI) ; Musen, M. (PI) ; Napel, S. (PI) ; Nolan, G. (PI) ; Owen, A. (PI) ; Owens, D. (PI) ; Paik, D. (PI) ; Palacios, J. (PI) ; Palaniappan, L. (PI) ; Pande, V. (PI) ; Petrov, D. (PI) ; Plevritis, S. (PI) ; Pohl, K. (PI) ; Poldrack, R. (PI) ; Pritchard, J. (PI) ; Relman, D. (PI) ; Rivas, M. (PI) ; Rose, S. (PI) ; Ross, E. (PI) ; Rubin, D. (PI) ; Sabatti, C. (PI) ; Salzman, J. (PI) ; Shachter, R. (PI) ; Shafer, R. (PI) ; Shah, N. (PI) ; Sherlock, G. (PI) ; Sidow, A. (PI) ; Snyder, M. (PI) ; Tang, H. (PI) ; Taylor, C. (PI) ; Tibshirani, R. (PI) ; Tu, S. (PI) ; Utz, P. (PI) ; Walker, M. (PI) ; Wall, D. (PI) ; Winograd, T. (PI) ; Witte, J. (PI) ; Wong, W. (PI) ; Xing, L. (PI) ; Yeung, S. (PI) ; Zou, J. (PI)

BIOMEDIN 370: Medical Scholars Research

Provides an opportunity for student and faculty interaction, as well as academic credit and financial support, to medical students who undertake original research. Enrollment is limited to students with approved projects.
Terms: Aut, Win, Spr, Sum | Units: 4-18 | Repeatable for credit
Instructors: Altman, R. (PI) ; Ashley, E. (PI) ; Bassik, M. (PI) ; Batzoglou, S. (PI) ; Bayati, M. (PI) ; Bejerano, G. (PI) ; Bhattacharya, J. (PI) ; Blish, C. (PI) ; Boahen, K. (PI) ; Brandeau, M. (PI) ; Bustamante, C. (PI) ; Butte, A. (PI) ; Chang, H. (PI) ; Chen, J. (PI) ; Cherry, J. (PI) ; Cohen, S. (PI) ; Covert, M. (PI) ; Das, A. (PI) ; Das, R. (PI) ; Davis, R. (PI) ; Delp, S. (PI) ; Desai, M. (PI) ; Dill, D. (PI) ; Dror, R. (PI) ; Dumontier, M. (PI) ; Elias, J. (PI) ; Fagan, L. (PI) ; Feldman, M. (PI) ; Ferrell, J. (PI) ; Fraser, H. (PI) ; Gerritsen, M. (PI) ; Gevaert, O. (PI) ; Goldstein, M. (PI) ; Greenleaf, W. (PI) ; Guibas, L. (PI) ; Hastie, T. (PI) ; Hlatky, M. (PI) ; Holmes, S. (PI) ; Ji, H. (PI) ; Karp, P. (PI) ; Khatri, P. (PI) ; Kim, S. (PI) ; Kirkegaard, K. (PI) ; Klein, T. (PI) ; Koller, D. (PI) ; Krummel, T. (PI) ; Kundaje, A. (PI) ; Levitt, M. (PI) ; Li, J. (PI) ; Longhurst, C. (PI) ; Lowe, H. (PI) ; Mallick, P. (PI) ; Manning, C. (PI) ; McAdams, H. (PI) ; Menon, V. (PI) ; Montgomery, S. (PI) ; Musen, M. (PI) ; Napel, S. (PI) ; Nolan, G. (PI) ; Owen, A. (PI) ; Owens, D. (PI) ; Paik, D. (PI) ; Palacios, J. (PI) ; Pande, V. (PI) ; Petrov, D. (PI) ; Plevritis, S. (PI) ; Poldrack, R. (PI) ; Pritchard, J. (PI) ; Relman, D. (PI) ; Rivas, M. (PI) ; Rubin, D. (PI) ; Sabatti, C. (PI) ; Salomon, J. (PI) ; Salzman, J. (PI) ; Shachter, R. (PI) ; Shafer, R. (PI) ; Shah, N. (PI) ; Sherlock, G. (PI) ; Sidow, A. (PI) ; Snyder, M. (PI) ; Tang, H. (PI) ; Taylor, C. (PI) ; Tibshirani, R. (PI) ; Tu, S. (PI) ; Utz, P. (PI) ; Walker, M. (PI) ; Wall, D. (PI) ; Winograd, T. (PI) ; Wong, W. (PI) ; Xing, L. (PI) ; Zou, J. (PI)

BIOMEDIN 390A: Curricular Practical Training

Terms: Aut, Win, Spr, Sum | Units: 1

BIOMEDIN 390B: Curricular Practical Training

Provides educational opportunities in biomedical informatics research. Qualified biomedical informatics students engage in internship work and integrate that work into their academic program. Students register during the quarter they are employed and must complete a research report outlining their work activity, problems investigated, key results, and any follow-up on projects they expect to perform. BIOMEDIN 390A, B, and C may each be taken only once.
Terms: Aut, Win, Spr, Sum | Units: 1
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