Summer School: How to understand data, how to combat diseases

Brandenburg an der Havel, 16 September 2024

This year’s Summer School offered practice-related insights into the analysis of medical data using Python and R as programming languages. Organizers of the Summer School entitled "Medical Data Analysis for Young Scientists" were medical IT expert Dennis Wagner from the MHB and pathologist Prof. Dr. med. Thomas Schrader, professor of medical computer science at Technische Hochschule Brandenburg. Prof. Schrader acted as instructor and supervisor during the event from 9 to 13 September.

The schedule covered various aspects of medical data analysis as follows:

Day 1: Introduction to medical data analysis
The event started with a welcome and presentation of the range of contents, followed by an introduction to programming languages Python and R. Participants attended live coding sessions where they learned to upload data for analysis and execute preliminary simple scripts on data processing and analysis. The first day provided a basis for the rest of the course and underlined the importance of a systematic approach to data handling.

Day 2: Explorative data analysis
The focus on the second day was on explorative data analysis (EDA). Visualizations and descriptive statistics were used to study data, identify patterns and test hypotheses. Subsequent practical exercises served to produced preliminary statistical plots and analyze trends and distributions.

Day 3: Data quality and cleansing
Analysis of data quality was the topic on the third day. Prof. Schrader illustrated how to detect outliers and missing values, and how to apply techniques of data cleansing. Participants practiced data cleansing in hands-on sessions in preparation of a meaningful analysis.

Day 4: Correlations and regression analysis
On the fourth day, the course addressed correlation analysis and regression analysis. Students learned to explore correlations between variables and develop forecasts via regression models. Prof. Schrader demonstrated applications of such techniques using Python and R and ways to get interpretable results.

Day 5: Pipeline of medical data analysis
The focus on the last day was on integration of acquired knowledge and skills into a coherent process. Participants worked with real-life medical data and developed a comprehensive pipeline of data analysis.

Dennis Wagner’s summary: “The Summer School 'Medical Data Analysis for Young Scientists' was highly successful. Students have acquired sound theoretical knowledge and gained practical experience in the analysis of real medical data. They have learned how to use Python and R and are well equipped to address research questions of their own choice.”