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Course leader: István Vassányi, PhD


The course addresses the problems of health data management and modelling, with a special emphasis on unstructured data and legal and economic aspects. It covers the specific requirements and methods of the problem domain in the field of data analysis. The problems will be illustrated with research results of the faculty. 


1. Types of health data, binary, structured, textual forms of data. Public health databases.

2. Processing of non-structured health documents, literature search, text analysis using automated methods 

3. Legal protection of health data, implications for data modelling and storage, anonymisation 

4. Population level analysis of health data, analysis of patient pathways and episodes, characterisation of the care system using spatial and network science methods 

5. Health care coding systems and their relation to care financing 

6. Data processing problems in clinical trials, typical data cleaning and analysis techniques.


  1. Lachin JM: Biostatistical methods. Assessment of Relative Risks.
  2. Dinya Elek: Biostatisztika az orvosi gyakorlatban. Medicina, Budapest, 2011.
  3. Giannopoulou EG. Data Mining in Medical and Biological Research InTech 2008, ( )
  4. Witten IH: Data Mining, Morgan Kaufmann Publishers, San Francisco, 1999.
  5. Daren G, Mallery P: IBM SPSS Statistics 19 Step by Step, 12th Edition, Pearson, Boston, 2012.
  6. Zoltán Alexin (2014) Does fair anonymization exist?, International Review of Law, Computers & Technology, 28:1, 21-44, DOI: 10.1080/13600869.2013.869909
  7. Scott Madry. Introduction to QGIS Open Source Geographic Information System. SBN (PDF) 978-1734464313, 2022.