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81 - 90 of 772 results for: Medicine

BIOE 236: Biophysical Mechanisms of Innate Immunity

This course teaches key biophysical aspects and mechanisms of the human innate immune system and its cellular and molecular effectors. We discuss the current understanding and hypotheses for how misregulation of innate immunity contribute to inflammatory and autoimmune conditions. Students and postdocs gain experience in the creative planning and writing of a technical paper on an intriguing topic in medicine using the primary literature as a resource, and practice giving lectures about the results of their research to their peers.
Terms: Win | Units: 3
Instructors: Barron, A. (PI)

BIOE 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOMEDIN 279, BIOPHYS 279, CME 279, CS 279)

Computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules and cells. These computational methods play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course topics include protein structure prediction, protein design, drug screening, molecular simulation, cellular-level simulation, image analysis for microscopy, and methods for solving structures from crystallography and electron microscopy data. Prerequisites: elementary programming background ( CS 106A or equivalent) and an introductory course in biology or biochemistry.
Terms: Aut | Units: 3

BIOE 361: Biomaterials in Regenerative Medicine (MATSCI 381)

Materials design and engineering for regenerative medicine. How materials interact with cells through their micro- and nanostructure, mechanical properties, degradation characteristics, surface chemistry, and biochemistry. Examples include novel materials for drug and gene delivery, materials for stem cell proliferation and differentiation, and tissue engineering scaffolds. Prerequisites: undergraduate chemistry, and cell/molecular biology or biochemistry.
Terms: Aut | Units: 3

BIOE 390: Introduction to Bioengineering Research (MED 289)

Preference to medical and bioengineering graduate students with first preference given to Bioengineering Scholarly Concentration medical students. Bioengineering is an interdisciplinary field that leverages the disciplines of biology, medicine, and engineering to understand living systems, and engineer biological systems and improve engineering designs and human and environmental health. Students and faculty make presentations during the course. Students expected to make presentations, complete a short paper, read selected articles, and take quizzes on the material.
Terms: Aut | Units: 1-2 | Repeatable for credit

BIOE 393: Bioengineering Departmental Research Colloquium

Required Bioengineering department colloquium for first year Ph.D. and M.S. students. Topics include applications of engineering to biology, medicine, biotechnology, and medical technology, including biodesign and devices, molecular and cellular engineering, regenerative medicine and tissue engineering, biomedical imaging, and biomedical computation.
Terms: Aut, Win | Units: 1 | Repeatable for credit

BIOE 459: Frontiers in Interdisciplinary Biosciences (BIO 459, BIOC 459, CHEM 459, CHEMENG 459, PSYCH 459)

Students register through their affiliated department; otherwise register for CHEMENG 459. For specialists and non-specialists. Sponsored by the Stanford BioX Program. Three seminars per quarter address scientific and technical themes related to interdisciplinary approaches in bioengineering, medicine, and the chemical, physical, and biological sciences. Leading investigators from Stanford and the world present breakthroughs and endeavors that cut across core disciplines. Pre-seminars introduce basic concepts and background for non-experts. Registered students attend all pre-seminars; others welcome. See http://biox.stanford.edu/courses/459.html. Recommended: basic mathematics, biology, chemistry, and physics.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit

BIOHOPK 14: Bio-logging and Bio-telemetry

Bio-logging is a rapidly growing discipline that includes diverse fields such as consumer electronics, medicine, and marine biology. The use of animal-attached digital tags is a powerful approach to study the movement and ecology of individuals over a wide range of temporal and spatial scales. This course is an introduction to bio-logging methods and analysis. Using whales as a model system, students will learn how use multi-sensor tags to study behavioral biomechanics.
Last offered: Spring 2018 | UG Reqs: WAY-AQR, WAY-SMA

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

BIOMEDIN 207: Seminar: Health IT in Care Delivery systems

The practice of medicine is reacting quickly to the avalanche of information available from electronic health records and data directly submitted by patients and from the environment. 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, medical education, and the innovation pipeline for healthcare delivery organizations.
Terms: Sum | Units: 1

BIOMEDIN 215: 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 graduate class will teach you how to use EHRs and other patient data to discover new clinical knowledge and improve healthcare. Upon completing this course, you should be able to: 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 an analysis of a clinical dataset based on your familiarity with the workings, applicability, and limitations of common statistical methods, evaluate and criticize published research using your knowledge of 1-4 to generate new research ideas and separate hype from reality. Prerequisites: CS 106A or equivalent, STATS 60 or equivalent. Recommended: STATS 216, CS 145, STATS 305
Terms: Aut | Units: 3
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