Bronchopulmonary Dysplasia Prediction Using Naive Bayes Classifier

The paper presents BPD (Bronchopulmonary Dysplasia) prediction for extremely premature infants after their first week of life. In contrast to the most works where LR (Logit Regression) is used, the naive Bayes classifier was proposed. Data was collected thanks to the Neonatal Intensive Care Unit of The Department of Pediatrics at Jagiellonian University Medical College and includes 109 patients with birth weight less than or equal to 1500 g. Fourteen different features were considered and all \(2^{14}\) of theirs combinations were analyzed. This paper also includes an accuracy and its deviation comparison with other prediction methods. It was possible because the calculations were performed on the very same data, which was used in previous works presenting LR and SVM forecasts.