Abstract
The problem of data classification with a statistical method is presented in the paper. Described classification method enables calculation of probability of disease incidence. A case of disease incidence is described with two parameters expressed in real numbers. The case can belong to a known set of cases where the disease occurred or to the set where the disease did not occur. A method for calculating probability with which a given case belongs to the set labeled as “1” or “0” is proposed. Source data used in the paper come from medical databases and are original. The algorithm of the method was checked on clinical cases. Correlation method was used for generating respective statistics. The calculated correlation at a level of 0.8 is indicative of disease occurrence, whereas the correlation coefficient at a level of 0.0 is indicative of the lack of disease. This property is used in the classification algorithm. It is frequent in the clinical practice that we have one test case and we try to determine whether or not that case describes symptoms of liability to the disease. Classification is related with the occurrence of Bronchopulmonary dysplasia, which is analyzed in a 3 to 4 week period preceding the disease incidence.
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© 2016 Springer International Publishing Switzerland
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Wajs, W., Wojtowicz, H., Wais, P., Ochab, M. (2016). Statistical Method for the Problem of Bronchopulmonary Dysplasia Classification in Pre-mature Infants. In: Czarnowski, I., Caballero, A., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2016. IDT 2016. Smart Innovation, Systems and Technologies, vol 56. Springer, Cham. https://doi.org/10.1007/978-3-319-39630-9_14
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DOI: https://doi.org/10.1007/978-3-319-39630-9_14
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Online ISBN: 978-3-319-39630-9
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