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- | ====== BIOMEDIN 215 DATA DRIVEN MEDICINE ====== | + | ====== BIOMEDIN 215, 2020 ====== |
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- | The widespread adoption of electronic health records (EHRs) has created a new source of “bigdata”—namely, the record of routine clinical practice—as a by-product of care. Can we use this data to save lives and promote wellbeing? | + | |
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- | Upon completing this course, you should be able to: | + | |
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- | - differentiate between and give examples of categories of research questions and the study designs used to address them. | + | |
- | - describe common healthcare data sources and their relative advantages and limitations. | + | |
- | - extract and transform various kinds of clinical data to create analysis-ready datasets. | + | |
- | - design and execute a statistical analysis of a clinical dataset to answer a research question. | + | |
- | - apply your knowledge to evaluate and criticize published clinical informatics research. | + | |
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- | The overall goal of this course is to prepare you to discover meaningful clinical knowledge using healthcare data. In addition, the practical skills you will learn in this class will be applicable to any task involving data manipulation and analysis. | + | |
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- | The course will use real, de-identified, | + | |
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- | **Prerequisites: | + | |
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- | ====== Schedule and Syllabus ====== | + | |
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- | **Schedule**: | + | |
- | **Course materials**: | + | |
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- | TAs: Ben Huynh (benhuynh AT stanford.edu), | + | |
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- | ^If nothing shows up in the space below, reload the page| | + | |
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- | < | + | |
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+ | In the Autumn quarter of 2020, this class will be very different compared to the [[biomedin215_precovid|pre-COVID]] offering and will be limited to graduate students in the Biomedical Informatics Program. |