Clinical Applications of Computational Medicine
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
EI7585 is a semester module in English language at Master’s level which is offered every semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
|Total workload||Contact hours||Credits (ECTS)|
|180 h||30 h||6 CP|
Content, Learning Outcome and Preconditions
They are able to apply basic signal processing techniques to solve specific problems (filtering and analysis of data from mobile accelerometry/ECG). They also should be able to understand the scientific method to conduct exploratory research generating and testing hypothesis, looking at events, collecting data, analyzing information and reporting the results. In addition, it is expected that they improve their written and oral communications skills by the creation of a scientific report and holding a public presentation.
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VO||2||Clinical Applications of Computational Medicine||
Assistants: Baumhoer, R.
and singular or moved dates
Learning and Teaching Methods
" Schimpl M, Moore C, Lederer C, Neuhaus A, Sambrook J, Danesh J, Ouwehand W, Daumer M: Association between walking speed and age in healthy, free-living individuals using mobile accelerometry - a cross-sectional study. PLoS ONE 6(8): e23299. doi:10.1371/journal.pone. 0023299
" Schimpl M, Lederer C, Daumer M: Development and validation of a new method to measure walking speed in free-living environments using the actibelt platform. PLoS ONE 6(8): e23080. doi:10.1371/journal.pone.0023080
" Scalfari A, Neuhaus A, Daumer M, Ebers GC, Muraro PA: Age and disability accumulation in Multiple Sclerosis. Neurology (published ahead of print September 14, 2011)
" Daumer M, Neuhaus A, Herbert J. Ebers G: Prognosis of the individual course of disease: the elements of time, hetereogeneity and precision, Journal of the Neurological Sciences 287: S50-S55, 2009
" Ebers G., Heigenhauser L., Daumer M., Lederer C., Noseworthy J.: Disability as an outcome in clinical trials . Neurology 71 (9), 624-631, 2008
" Daumer M, Held U, Ickstadt K, Heinz M, Schach S, Ebers G: Reducing the Probability of false positive Research Findings by pre-publication Validation Experience with a large Multiple Sclerosis Database. BMC Medical Research Methodology 8:18, 2008
" Schunkert, H. et al. for the Cardiogenics Consortium: Repeated Replication and a Prospective Meta-Analysis of the Association Between Chromosome 9p21.3 and Coronary Artery Disease. Circulation 117, 1675-1684, 2008
" Daumer M, Scholz M, Boulesteix AL, Pildner von Steinburg S, Schiermeier S, Hatzmann W, Schneider KTM: The Normal Fetal Heart Rate Study: Analysis Plan , Available at Nature Precedings http://precedings.nature.com/documents/980/version/2, 2007
" Daumer M., Neuhaus A., Lederer C., Scholz M., Wolinsky JS and Heiderhoff M.: Prognosis of the individual course of disease steps in developing a decision support tool for Multiple Sclerosis. BMC Medical Informatics and Decision Making 2007, 7:11
" Daumer M, Thaler K, Kruis E, Feneberg W, Staude G, Scholz M: Steps towards a miniaturized, robust and autonomous measurement device for the long-term monitoring of the activity of patients ActiBelt . Biomedizinische Technik, Biomedical Engineering 52: 149-55, 2007
" Noseworthy J., Kappos L., Daumer M.: Competing interests in Multiple Sclerosis research , The Lancet 361, S. 350f, 2003
" Daumer M.: Online Monitoring von Changepoints in: Biomedizinische Technik, 42, Ergänzungsband 2, Verlag Schiele und Schön, S. 214-215, 1998
" Daumer M., Nahm W., Scholz M., Dannegger F., Kochs E., Morfill G.: Konzept für eine internet-basierte Datenbank zur Unterstützung von Projekten in der Biosignalanalyse , Ergänzungsband Biomed Tech, 43 (3), S. 23-27, 1998
Description of exams and course work
In general, a project encompasses these tasks: study design, data collection, algorithm development and validation, data analysis and summary of results.
Students should prepare a report (maximum 4 pages) including the details of their work as well as a set of slides for the final presentation. The The results will be presented to the audience and defended at the end of the semester. External guests are invited to attend and participate in the final presentation.
The quality of the written report, the presentation and the discussion contribute each as 1/3 of the final grade.
There is a possibility to take the exam in the following semester.