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Clinical Applications of Computational Medicine

Course 0000002166 in WS 2018/9

General Data

Course Type lecture
Semester Weekly Hours 2 SWS
Organisational Unit Chair of Data Processing (Prof. Diepold)
Lecturers Martin Daumer
Assistants:
Peter Hausamann
Dates Thu, 16:45–18:15, 0938

Assignment to Modules

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks ECTS credits = 6 Computational medicine is a new scientific field in the intersection between mathematics, physics, biostatistics, computer science, electronics, biomedical engineering and medicine. In this lecture we will focus on actual clinical applications of computational medicine using examples from areas like multiple sclerosis, obstetrics, coronary artery disease and sport medicine. After a short introduction and description about potential and current topics of interest in the medical clinical field the students work in small groups under the guidance of tutors/lecturers/external experts on self-selected projects in the area of "computational medicine". Students are encouraged to build prototypes using the modern technologies available -- sensors, webservices, smartphones, etc -- with the aim to provide solutions to current shortfalls in the clinical practice or in the sports science field. Project topics Topics of "Clinical Applications of Computational Medicine" are: 1 "Mobile accelerometry" ("Natural Running", "Move Your Heath", "Fall Risk Prediction", "Fall detection") 2 "Fetal Heart Monitoring" 3 "Evidence Based Decision Support in Multiple Sclerosis" 4 "Validation in large Biomedical Databases"
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interactive examples
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