Abstract
The work presents the results of inconsistency detection ex- periments on the data records of an atherosclerotic coronary heart disease database collected in the regular medical practice. Medical expert evalu- ation of some preliminary inductive learning results have demonstrated that explicit detection of outliers can be useful for maintaining the data quality of medical records and that it might be a key for the improvement of medical decisions and their reliability in the regular medical practice. With the intention of on-line detection of possible data inconsistences, sets of confirmation rules have been developed for the database and their test results are reported in this work.
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Gamberger, D., Lavrač, N., Krstačić, G., Śmuc, T. (2000). Incosistency Tests for Patient Records in a Coronary Heart Disease Database. In: Brause, R.W., Hanisch, E. (eds) Medical Data Analysis. ISMDA 2000. Lecture Notes in Computer Science, vol 1933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39949-6_22
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DOI: https://doi.org/10.1007/3-540-39949-6_22
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