printer friendly pageCHPR 260: Prevention Across Medical Disciplines: Evidence-based Guidelines
Coordinated seminar series presenting evidence-based health promotion and disease prevention guidelines by research and clinical faculty of multiple divisions of Stanford's Department of Medicine, including cardiovascular medicine, oncology, nephrology, immunology and rheumatology, infectious diseases, endocrinology, gerontology and metabolism, gastroenterology and hepatology, hematology, blood and marrow transplantation, pulmonary and critical care medicine, general medical disciplines (including family medicine). Key prevention issues addressed in primary care and outcomes research, biomedical informatics research and the Stanford Prevention Research Center also presented. Enrollment priority given to CHPR Master's students. CHPR students must enroll for letter grade.Prerequisite:
CHPR 201 or
HUMBIO 126/
CHPR 226 or equivalent or consent of instructor.
Terms: Win
| Units: 3
Instructors:
Stefanick, M. (PI)
CHPR 270: Prevention Across Surgical and Other Medical Disciplines
This course is coordinated seminar series that presents evidence-based health promotion and disease prevention guidelines by clinical and translational research and population health science faculty of clinical departments other than Medicine (the focus of
CHPR 260) of the Stanford School of Medicine, including; Anesthesiology & Perioperative, & Pain Medicine, Cardiothoracic Surgery, Dermatology, Emergency Medicine, Neurology & Neurological Sciences, Neurosurgery, Obstetrics & Gynecology, Ophthalmology, Orthopaedic Surgery, Otolaryngology, Pathology, Pediatrics, Psychiatry & Behavioral Sciences, Radiation Oncology, Radiology, Surgery and Urology, CHPR master's program students must enroll for a letter grade and priority for enrollment will be given to current CHPR students. Prerequisites:
CHPR 201 or
HUMBIO 126/
CHPR 226 or equivalent or consent of instructor.
Terms: Spr
| Units: 3
Instructors:
Stefanick, M. (PI)
CHPR 291: Assessing the Health Effects of Economic Change
This practicum will involve students as managers of real-time study of the health effects of minimum wage changes in the Bay Area. A long-held economic theory suggests that increased income should have secondary benefits to health, particularly for mental health and adverse health behaviors (e.g., binge drinking). Recent increases in the minimum wage in the Bay Area provide a rare opportunity to test this theory. Students in this course will participate in organizing, executing and directing a community-based study of the health effects of minimum wage increases among local cities, under close guidance and supervision of Stanford faculty in medicine, health economics and sociology. Students will engage in class meetings one hour per week to learn classical and novel methods for the analysis of natural experiments in health policy and economics (e.g., different-in-differences methods, synthetic control analysis), and are expected to participate in directed field-based group projects for several additional hours per week. Priority will be given to students with interest and experience in community-based research on social determinants of health and with bilingual English/Spanish speaking skills. Prerequisites: A course in statistics. Students will be expected to travel off campus to area of Santa Clara and San Mateo counties accessible via Marguerite shuttle, BART/Caltrain or VTA bus. The group work involves recruiting and surveying low-income community members, and requires tenacity to conduct field-based studies.
Last offered: Autumn 2016
CLASSICS 14: Greek and Latin Roots of English
(Formerly
CLASSGEN 9) Goal is to improve vocabulary, comprehension of written English, and standardized test scores through learning the Greek and Latin components of English. Focus is on patterns and processes in the formation of the lexicon. Terminology used in medicine, business, education, law, and humanities; introduction to principles of language history and etymology. Greek or Latin not required.
Terms: Sum
| Units: 3
Instructors:
Epstein, N. (PI)
CLASSICS 34: Ancient Athletics
(Formerly
CLASSGEN 34.) How the Olympic Games developed and how they were organized. Many other Greek festivals featured sport and dance competitions, including some for women, and showcased the citizen athlete as a civic ideal. Roman athletics in contrast saw the growth of large-scale spectator sports and professional athletes. Some toured like media stars; others regularly risked death in gladiatorial contests and chariot-racing. We will also explore how large-scale games were funded and how they fostered the development of sports medicine. Weekly participation in a discussion section is required; enroll in sections on coursework.
Terms: Win
| Units: 3-4
| UG Reqs: GER:DB-Hum, WAY-A-II, WAY-SI
CLASSICS 123: Ancient Medicine
Contemporary medical practice traces its origins to the creation of scientific medicine by Greek doctors such as Hippocrates and Galen. Is this something of which modern medicine can be proud? The scientific achievements and ethical limitations of ancient medicine when scientific medicine was no more than another form of alternative medicine. Scientific medicine competed in a marketplace of ideas where the boundaries between scientific and social aspects of medicine were difficult to draw.
Terms: Aut
| Units: 3-4
| UG Reqs: GER:DB-Hum, WAY-SI
Instructors:
Netz, R. (PI)
CLASSICS 124: Ancient and Modern Medicine
Imagine a world where the Universe has a built-in purpose and point. How would this belief impact man's place in nature? Imagine a world where natural substances have "powers." How might this impact diet and pharmacology? Magical vs. scientific healing: a clear divide? Disease and dehumanization: epilepsy, rabies. Physical and mental health: black bile and melancholy. The ethical and scientific assumptions hidden in medical language and imagery. How ancient medicine and modern medicine (especially alternative medicine) illuminate each other.
Last offered: Spring 2016
| UG Reqs: GER:DB-Hum
CME 106: Introduction to Probability and Statistics for Engineers (ENGR 155C)
Probability: random variables, independence, and conditional probability; discrete and continuous distributions, moments, distributions of several random variables. Topics in mathematical statistics: random sampling, point estimation, confidence intervals, hypothesis testing, non-parametric tests, regression and correlation analyses; applications in engineering, industrial manufacturing, medicine, biology, and other fields. Prerequisite:
CME 100/ENGR154 or
MATH 51 or 52.
Terms: Win, Sum
| Units: 4
| UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
Instructors:
Khayms, V. (PI)
;
Amidi, S. (TA)
;
Chen, G. (TA)
;
Chhor, G. (TA)
;
Chu, C. (TA)
;
Lakshman, V. (TA)
;
Pyron, J. (TA)
;
Sagastuy Brena, J. (TA)
;
Wu, Y. (TA)
CME 279: Computational Biology: Structure and Organization of Biomolecules and Cells (BIOE 279, BIOMEDIN 279, BIOPHYS 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
Instructors:
Dror, R. (PI)
;
Bedi, R. (TA)
;
El-Gabalawy, O. (TA)
...
more instructors for CME 279 »
Instructors:
Dror, R. (PI)
;
Bedi, R. (TA)
;
El-Gabalawy, O. (TA)
;
Fernandes, D. (TA)
;
Paggi, J. (TA)
;
Sanborn, A. (TA)
CME 371: Computational Biology in Four Dimensions (BIOMEDIN 371, BIOPHYS 371, CS 371)
Cutting-edge research on computational techniques for investigating and designing the three-dimensional structure and dynamics of biomolecules, cells, and everything in between. These techniques, which draw on approaches ranging from physics-based simulation to machine learning, play an increasingly important role in drug discovery, medicine, bioengineering, and molecular biology. Course is devoted primarily to reading, presentation, discussion, and critique of papers describing important recent research developments. Prerequisite:
CS 106A or equivalent, and an introductory course in biology or biochemistry. Recommended: some experience in mathematical modeling (does not need to be a formal course).
Terms: Win
| Units: 3
Instructors:
Dror, R. (PI)
Filter Results: