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111 - 120 of 561 results for: Medicine

CS 102: Big Data: Tools and Techniques, Discoveries and Pitfalls

Aimed primarily at students who may not major in CS but want to learn about big data and apply that knowledge in their areas of study. Many of the world's biggest discoveries and decisions in science, technology, business, medicine, politics, and society as a whole, are now being made on the basis of analyzing massive data sets, but it is surprisingly easy to come to false conclusions from data analysis alone, and privacy of data connected to individuals can be a major concern. This course provides a broad introduction to big data: historical context and case studies; privacy issues; data analysis techniques including databases, data mining, and machine learning; sampling and statistical significance; data analysis tools including spreadsheets, SQL, Python, R; data visualization techniques and tools. Tools and techniques are hands-on but at a cursory level, providing a basis for future exploration and application. Prerequisites: high school AP computer science, CS106A, or other equivalent programming experience; comfort with statistics and spreadsheets helpful but not required.
Terms: Spr | Units: 3-4 | UG Reqs: WAY-AQR

CS 231N: Convolutional Neural Networks for Visual Recognition

Computer Vision has become ubiquitous in our society, with applications innsearch, image understanding, apps, mapping, medicine, drones, andnself-driving cars. Core to many of these applications are the tasks of image classification, localization and detection. This course is a deep dive into details of neural network architectures with a focus on learning end-to-end models for these tasks, particularly image classification. During the 10-week course, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. The final assignment will involve training a multi-million parameter convolutional neural network and applying it on the largest image classification dataset (ImageNet). We will focus on teaching how to set up the problem of image recognition, the learning algorithms (e.g. backpropagation), practical engineering tricks for training and fine-tuning the networks and guide the students through hands-on assignments and a final course project. Much of the background and materials of this course will be drawn from the ImageNet Challenge: http://image-net.org/challenges/LSVRC/2014/index. Prerequisites: Proficiency in Python; familiarity with C/C++; CS 131 and CS 229 or equivalents; Math 21 or equivalent, linear algebra.
Terms: Win | Units: 3-4

CS 275: Translational Bioinformatics (BIOMEDIN 217)

Analytic, storage, and interpretive methods to optimize the transformation of genetic, genomic, and biological data into diagnostics and therapeutics for medicine. Topics: access and utility of publicly available data sources; types of genome-scale measurements in molecular biology and genomic medicine; analysis of microarray data; analysis of polymorphisms, proteomics, and protein interactions; linking genome-scale data to clinical data and phenotypes; and new questions in biomedicine using bioinformatics. Case studies. Prerequisites: programming ability at the level of CS 106A and familiarity with statistics and biology.
Terms: Win | Units: 4

CS 309A: Cloud Computing

For science, engineering, business, medicine, and law students. Cloud computing is bringing information systems out of the back office and making it core to the entire economy. This class is intended for all students who want to begin to understand the implications of this shift in technology. Guest industry experts are public company CEOs who are delivering application, software development, operations management, compute, storage & data center, and network cloud services.
Terms: Aut | Units: 1 | Repeatable for credit
Instructors: Chou, T. (PI)

CS 379C: Computational Models of the Neocortex

Reprisal of course offered spring 2012 of the same name ; see http://www.stanford.edu/class/cs379c/ for more detail ; which emphasized scaling the technologies of systems neuroscience to take advantage of the exponential trend in computational power known as Moore's Law. Course covers many of the same topics but will focus on the near-term prospects for practical advances in health care, prosthetic augmentation, and artificial intelligence inspired by biological systems. Graded pass / no credit on the basis of class participation, a midterm white paper or business prospectus and a final technical report evaluating an appropriate technology selected in collaboration with the instructor. Focus will be on examining the assumptions underlying current claims for realizing the potential benefits of research in neuroscience and identifying real business opportunities, disruptive new technologies and advances in medicine that could substantially benefit patients within the next decade. Technology-minded critical thinkers seriously interested in placing their bets and picking careers in related areas of business, technology and science are welcome. Prerequisites: basic probability theory, algorithms, and statistics.
Terms: Spr | Units: 3
Instructors: Dean, T. (PI)

CS 571: Surgical Robotics Seminar (ME 571)

Surgical robots developed and implemented clinically on varying scales. Seminar goal is to expose students from engineering, medicine, and business to guest lecturers from academia and industry.engineering and clinical aspects connected to design and use of surgical robots, varying in degree of complexity and procedural role. May be repeated for credit.
Last offered: Spring 2015 | Repeatable for credit

CSP 261: The Organic Chemistry of Life: Understanding Medicine and Drugs

CSRE 66: SPECTACULAR TRIALS: SEX, RACE AND VIOLENCE IN MODERN AMERICAN CULTURE (AMSTUD 106)

This course will use the phenomenon of the spectacular trial as a framework for exploring the intersections of sex, race, and violence in the formation of modern American culture. Beginning in the late nineteenth century and continuing through the 1990s, we will focus our inquiry on a number of notorious cases, some associated with familiar names¿the ¿Scottsboro Boys,¿ Emmett Till, O.J. Simpson¿others involving once-infamous actors¿like Joan Little and Inez Garcia¿whose ordeals have receded into historical memory, considering a range of questions arising from this thematic nexus. For instance, in what ways are sexual transgressions racialized and gendered? What are the practical and theoretical ramifications of the seemingly inextricable conjunction of sex and violence in legal and popular discourse? And what insights might such spectacles afford when broached as an arena in which sexual meanings, identities, and practices are refracted and ultimately constructed? We will also examine the role of the pertinent professions in the evolution of these events, in particular how the interplay of law, medicine, psychiatry, and forensic science helped define the shifting boundaries of legality, and how print, radio, and television journalism operated not only in sensationalizing, but also in reflecting, modeling, and shaping prevailing attitudes and behaviors. Our study of this vital facet of our ¿society of the spectacle¿ will draw on a series of compelling secondary readings complemented by a diverse array of primary sources¿from contemporaneous pamphlets and newspaper accounts to photographs, letters, trial testimony, and psychological commentary¿that will enable class members to evaluate the strengths and weaknesses of different textual genres, experiment with alternative methods of fashioning historical interpretations, and contemplate the ways history might be employed to illuminate the persistent problems of racial bias, reflexive sexualization, and the packaging of trials as mass entertainment in the present day.
Terms: Win | Units: 5
Instructors: Cardyn, L. (PI)

CSRE 69M: Race, Science, and Medicine in U.S. History (FEMGEN 69S, HISTORY 69S)

How have scientific ideas about race been shaped by their historical contexts, and what effects do these ideas have on people, institutions, law, and medicine? Is racial science always racist science? How do ideas about race intersect with ideas about gender, class, and disability? This course explores how natural philosophers and scientists have defined, used, and sometimes challenged ideas about race from the eighteenth century to today. Topics include medicine and slavery, eugenics, sociology, psychiatry, race-based medicine, and genetic ancestry. This course fulfills the departmental Sources and Methods requirement. Priority given to history majors and minors.
Terms: Spr | Units: 5 | UG Reqs: WAY-ED, WAY-SI
Instructors: LeBlanc, H. (PI)

CSRE 123B: Literature and Human Experimentation (AFRICAAM 223, COMPLIT 223, HUMBIO 175H, MED 220)

This course introduces students to the ways literature has been used to think through the ethics of human subjects research and experimental medicine. We will focus primarily on readings that imaginatively revisit experiments conducted on vulnerable populations: namely groups placed at risk by their classification according to perceived human and cultural differences. We will begin with Mary Shelley's Frankenstein (1818), and continue our study via later works of fiction, drama and literary journalism, including Toni Morrison's Beloved, David Feldshuh's Miss Evers Boys, Hannah Arendt's Eichmann and Vivien Spitz's Doctors from Hell, Rebecca Skloot's Immortal Life of Henrietta Lacks, and Kazuo Ishiguro's Never Let Me Go. Each literary reading will be paired with medical, philosophical and policy writings of the period; and our ultimate goal will be to understand modes of ethics deliberation that are possible via creative uses of the imagination, and literature's place in a history of ethical thinking about humane research and care.
Terms: Spr | Units: 3-5 | UG Reqs: GER:DB-Hum, GER:EC-EthicReas, WAY-A-II, WAY-ER
Instructors: Ikoku, A. (PI)
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