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1 - 6 of 6 results for: MED 219

BIOMEDIN 219: Mathematical Models and Medical Decisions

Analytic methods for determining optimal diagnostic and therapeutic decisions with applications to the care of individual patients and the design of policies applied to patient populations. Topics include: utility theory and probability modeling, empirical methods for disease prevalence estimation, probability models for periodic processes, binary decision-making techniques, Markov models of dynamic disease state problems, utility assessment techniques, parametric utility models, utility models for multidimensional outcomes, analysis of time-varying clinical outcomes, and the design of cost-constrained clinical policies. Extensive problem sets compliment the lectures. Prerequisites: introduction to calculus and basic statistics.
Terms: Win | Units: 3 | Grading: Medical Option (Med-Ltr-CR/NC)

BIOS 219: Human Gene Regulation: Genomic Thinking and Genomic Tools for Experimentalists

Focused look at the promoter/enhancer and related landscape of the human genome. Genomics and epigenomics of human gene regulation - truth, myths and mysteries. Genomic tools for the interpretation of vertebrate gene regulation experiments and predictions, and the insights behind them. Genomic thinking: purity vs. comprehensiveness, genome-wide vs. single locus. Prerequisites: undergraduate Biology or equivalent. Programming skills not required or taught.
Terms: not given this year | Units: 1 | Grading: Letter or Credit/No Credit

DBIO 219: Special Topics in Development and Cancer: Evolutionary and Quantitative Perspectives (BIOE 219)

The course will serve as a literature-based introductory guide for synthesis of ideas in developmental biology and cancer, with an emphasis on evolutionary analysis and quantitative thinking. The goal for this course is for students to understand how we know what we know about fundamental questions in the field of developmental biology and cancer, and how we ask good questions for the future. We will discuss how studying model organisms has provided the critical breakthroughs that have helped us understand developmental and disease mechanisms in higher organisms. The students are expected to be able to read the primary literature and think critically about experiments to understand what is actually known and what questions still remain unanswered. Students will develop skills in the educated guesswork to apply order-of-magnitude methodology to questions in development and cancer.
Terms: Win | Units: 3 | Grading: Letter (ABCD/NP)
Instructors: Wang, B. (PI)

FAMMED 219: Mind-Body Medicine

A small group (8-10) of medical students experientially exploring of the interconnections among human capacities such as thought, emotion, belief, attitudes, and physical health. Review and practice of specific skills (including mindfulness exercises, meditation, imagery, visualization, body awareness, autogenics, and biofeedback) to enhance self-awareness, self-expression, and stress management. Readings relevant to mind-body medicine made available. Anticipated benefits to class participants include discovering and mobilizing their capacity to participate in valuable and proven methods of self knowledge and stress reduction, while dealing with the frustrations and alienation that many students experience in medical school and beyond.
Terms: Spr | Units: 1 | Grading: Medical Option (Med-Ltr-CR/NC)

HRP 219: Evaluating Technologies for Diagnosis, Prediction and Screening

New technologies designed to monitor and improve health outcomes are constantly emerging, but most fail in the clinic and in the marketplace because relatively few are supported by reliable, reproducible evidence that they produce a health benefit. This course covers the designs and methods that should be used to evaluate technologies to diagnose patients, predict prognosis or other health events, or screen for disease. These technologies can include devices, statistical prediction rules, biomarkers, gene panels, algorithms, imaging, or any information used to predict a future or a previously unknown health state. Specific topics to be covered include the phases of test development, how to frame a proper evaluation question, measures of test accuracy, Bayes theorem, internal and external validation, prediction evaluation criteria, decision analysis, net-utility, ROC curves, c-statistics, net reclassification index, decision curves and reporting standards. Examples of technology assessm more »
New technologies designed to monitor and improve health outcomes are constantly emerging, but most fail in the clinic and in the marketplace because relatively few are supported by reliable, reproducible evidence that they produce a health benefit. This course covers the designs and methods that should be used to evaluate technologies to diagnose patients, predict prognosis or other health events, or screen for disease. These technologies can include devices, statistical prediction rules, biomarkers, gene panels, algorithms, imaging, or any information used to predict a future or a previously unknown health state. Specific topics to be covered include the phases of test development, how to frame a proper evaluation question, measures of test accuracy, Bayes theorem, internal and external validation, prediction evaluation criteria, decision analysis, net-utility, ROC curves, c-statistics, net reclassification index, decision curves and reporting standards. Examples of technology assessments and original methods papers are used. Software used in the course is R or Stata. Open to graduate students with a solid understanding of introductory biostatistics, epidemiologic and clinical research study design, and of medical conditions and related technologies required. Basic understanding of Stata or R is also required. Undergraduates may enroll with consent of instructor.
Terms: Win | Units: 3 | Grading: Medical Option (Med-Ltr-CR/NC)
Instructors: Goodman, S. (PI)

MED 219: What Patients and Families Want You to Know About Becoming Their Doctor

You will learn directly from patients and families about whole-person care, including topics such as compassion, challenging conversations, shared decision-making and end-of-life care. Patients, families, hospital staff and medical students will co-teach this course. The goal is to develop knowledge that enables you to keep the perspective and needs of patients, families, and personal caregivers as a primary focus, while operating within the complex reality of practicing medicine. By the end, you will have sharpened your ability to partner with patients and families as part of their care team and develop a more meaningful practice.
Terms: Aut | Units: 1 | Grading: Medical Satisfactory/No Credit
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