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1 - 10 of 14 results for: ANES ; Currently searching offered courses. You can also include unoffered courses

ANES 70Q: Critical Illness: Patients, Physicians, and Society

Examines the various factors involved in shaping the critical care illness experience for three groups of people: the clinicians, the patients, and patients' families. Medical issues, economic forces and cost concerns, cultural biases, and communication errors can all influence one's perception. Helps students understand the arc of critical illness, and how various factors contribute to the interactions between those various groups. Includes an immersion experience (students are expected to round with clinicians in the ICU and to attend Schwartz rounds, a debriefing meeting about difficult emotional situation) and a mentoring experience (with critical care fellows), in addition to routine class work.
Terms: Spr | Units: 3 | Grading: Satisfactory/No Credit

ANES 72Q: The Art of Medical Diagnosis

The Art of Medical Diagnosis: Enhancing Observational Skills through the Study of Art is an interactive, multidisciplinary undergraduate course that explores various ways in which studying art increases critical observational skills vital for aspiring health care providers. Students will be introduced to the concept of `Visual Thinking Strategies¿ through classroom, art creation, and museum based activities. Students will apply these skills to both works of art and medical cases. Significant focus will be on engaging in group discussions where they will collaboratively use visual evidence to generate and defend hypothesis. Drawing and sketching from life will play a critical role in honing observational skills through weekly assignments, workshops, and a final project. The interactive nature of this course pivots students away from a typical lecture based course to a self-directed learning experience.
Terms: Spr | Units: 3 | UG Reqs: WAY-CE | Grading: Letter or Credit/No Credit

ANES 199: Undergraduate Research

Allows for qualified students to undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: Anderson, T. (PI) ; Angelotti, T. (PI) ; Angst, M. (PI) ; Barr, J. (PI) ; Berhow, M. (PI) ; Bertaccini, E. (PI) ; Bhandari, R. (PI) ; Bohman, B. (PI) ; Boltz, M. (PI) ; Braitman, L. (PI) ; Brock-Utne, J. (PI) ; Brodsky, J. (PI) ; Butwick, A. (PI) ; Carroll, I. (PI) ; Caruso, T. (PI) ; Carvalho, B. (PI) ; Char, D. (PI) ; Chen, M. (PI) ; Cheung, A. (PI) ; Chu, L. (PI) ; Clark, D. (PI) ; Claure, R. (PI) ; Clements, F. (PI) ; Cohen, S. (PI) ; Collins, J. (PI) ; Cornaby, T. (PI) ; Darnall, B. (PI) ; Doufas, A. (PI) ; Drover, D. (PI) ; Fanning, R. (PI) ; Feaster, W. (PI) ; Fischer, S. (PI) ; Flood, P. (PI) ; Foppiano, L. (PI) ; Furukawa, L. (PI) ; Gaba, D. (PI) ; Gaudilliere, B. (PI) ; Giffard, R. (PI) ; Goldhaber-Fiebert, S. (PI) ; Golianu, B. (PI) ; Good, J. (PI) ; Gross, E. (PI) ; Haddow, G. (PI) ; Hammer, G. (PI) ; Hanowell, L. (PI) ; Harrison, T. (PI) ; Hill, C. (PI) ; Honkanen, A. (PI) ; Horn, J. (PI) ; Howard, S. (PI) ; Jackson, E. (PI) ; Jaffe, R. (PI) ; Kamra, K. (PI) ; Kanevsky, M. (PI) ; Kaufman, D. (PI) ; Kirz, J. (PI) ; Krane, E. (PI) ; Kuan, C. (PI) ; Kulkarni, V. (PI) ; Lemmens, H. (PI) ; Leong, M. (PI) ; Lighthall, G. (PI) ; Lipman, S. (PI) ; MacIver, M. (PI) ; Macario, A. (PI) ; Mackey, S. (PI) ; Malott, K. (PI) ; Mariano, E. (PI) ; McGregor, D. (PI) ; Mihm, F. (PI) ; Mora-Mangano, C. (PI) ; Mudumbai, S. (PI) ; Nekhendzy, V. (PI) ; Oakes, D. (PI) ; Pai Cole, S. (PI) ; Patterson, D. (PI) ; Pearl, R. (PI) ; Peltz, G. (PI) ; Pollard, J. (PI) ; Prasad, R. (PI) ; Ramamoorthy, C. (PI) ; Ramamurthi, R. (PI) ; Ratner, E. (PI) ; Riley, E. (PI) ; Robbins, W. (PI) ; Rodriguez, S. (PI) ; Rosenthal, M. (PI) ; Saidman, L. (PI) ; Sarnquist, F. (PI) ; Sastry, S. (PI) ; Scherrer, G. (PI) ; Schmiesing, C. (PI) ; Shafer, A. (PI) ; Shafer, S. (PI) ; Simons, L. (PI) ; Singh, V. (PI) ; Tanaka, P. (PI) ; Traynor, A. (PI) ; Trudell, J. (PI) ; Vokach-Brodsky, L. (PI) ; Williams, G. (PI) ; Wise-Faberowski, L. (PI) ; Yeomans, D. (PI) ; Younger, J. (PI) ; van der Starre, P. (PI)

ANES 205: Engage and Empower Me: Myths and Truths of Designing for Patient Behavior

Focus is on patient stories and real-life experiences of patient engagement, the neuroscience of behavior change and the principles of patient engagement.Together with patients, students participate in design sessions at Stanford¿s simulation center to create and test ways to modify behavior through design. Topics include the neuroscience behind motivating individuals into healthy behaviors, including patients in the care design process, how health educators, designers, techies and investors can improve success. Students enrolling for 3 units complete a class project.
Terms: not given this year | Units: 2-3 | Grading: Medical Option (Med-Ltr-CR/NC)

ANES 207: Medical Acupuncture

Acupuncture is part of a comprehensive system of traditional Chinese Medicine developed over the past two millennia. This course reviews the history and theoretical basis of acupuncture for the treatment of various diseases as well as for the alleviation of pain. Issues related to the incorporation of acupuncture into the current health care system and the efficacy of acupuncture in treating various diseases are addressed. Includes practical, hands-on sections.
Terms: Spr | Units: 2 | Grading: Medical Satisfactory/No Credit
Instructors: Golianu, B. (PI)

ANES 208A: Data Science for Digital Health and Precision Medicine

How will digital health, low-cost patient-generated and genomic data enable precision medicine to transform health care? This Everyone Included¿ course from Stanford Medicine X and SHC Clinical Inference will provide an overview of data science principles and showcase real world solutions being created to advance precision medicine through implementation of digital health tools, machine learning and artificial intelligence approaches. This class will feature thought leaders and luminaries who are patients, technologists, providers, researchers and leading innovators from academia and industry. This course is open to undergraduate and graduate students. Lunch will be provided.
Terms: Aut | Units: 1-2 | Repeatable for credit | Grading: Medical Option (Med-Ltr-CR/NC)

ANES 211SI: Themes in the History of Science and Medicine

What exactly is a diagnosis, and what is the history of that term? Why do Institutional Review Boards exist, and what atrocities in human medical experimentation occurred to prompt their creation? What is the role of narrative, social construction, and storytelling in medicine? This course will shed light on the ways physicians and scholars grapple with these and other important questions through a series of lectures from historians and philosophers of science, as well as bioethicists and scholars of narrative medicine. These perspectives on how scientific knowledge emerges and changes over time offer invaluable insights and frameworks for anyone aspiring to practice medicine or contribute to the collective body of scientific knowledge.
Terms: Aut | Units: 1 | Grading: Medical Satisfactory/No Credit

ANES 212: Machine Learning for Healthcare Quality: Precision Medicine Al Design Lab

This course provides a hands-on introduction to building machine learning systems for healthcare quality analysis and improvement. We explore several unconditional topics, including data representation, data manipulation, data analysis and data visualization. Students will be introduced to these topics during lectures. The course also provides students with a significant opportunity to investigate the application of these ideas to real-world clinical quality improvement challenges. Working with clinical mentors from the Stanford University School of Medicine students will be expected to supplement machine learning theory with a quarter-long project targeting representative clinical quality improvement challenges. Students will be encouraged to think creatively about traditionally hard quality problems and requires to perform group research exposing them to designing practical machine learning systems for healthcare.
Terms: Spr | Units: 3 | Repeatable for credit | Grading: Medical Option (Med-Ltr-CR/NC)

ANES 215: Journal Club for Neuroscience, Behavior and Cognition Scholarly Concentration

Review of current literature in both basic and clinical neuroscience in a seminar format consisting of both faculty and student presentations.
Terms: Win | Units: 1 | Repeatable for credit | Grading: Medical School MD Grades
Instructors: Yeomans, D. (PI)
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