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Bronchopulmonary Dysplasia Prediction Using Naive Bayes Classifier

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Advanced Solutions in Diagnostics and Fault Tolerant Control (DPS 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 635))

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Abstract

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.

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Authors and Affiliations

  1. The University of Rzeszów, Rzeszów, Poland

    Wiesław Wajs, Marcin Ochab, Kamil Trojnar & Hubert Wojtowicz

  2. State Higher Vocational School in Krosno, Krosno, Poland

    Piotr Wais

Authors
  1. Wiesław Wajs
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  2. Marcin Ochab
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  3. Piotr Wais
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  4. Kamil Trojnar
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  5. Hubert Wojtowicz
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Corresponding author

Correspondence to Marcin Ochab .

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Editors and Affiliations

  1. Faculty of Mechatronics, Institute of Automatic Control and Robotics, Warsaw University of Technology, Warsaw, Poland

    Jan M. Kościelny

  2. Faculty of Mechatronics, Institute of Automatic Control and Robotics, Warsaw University of Technology, Warsaw, Poland

    Michał Syfert

  3. Faculty of Mechatronics, Institute of Automatic Control and Robotics, Warsaw University of Technology, Warsaw, Poland

    Anna Sztyber

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Wajs, W., Ochab, M., Wais, P., Trojnar, K., Wojtowicz, H. (2018). Bronchopulmonary Dysplasia Prediction Using Naive Bayes Classifier. In: Kościelny, J., Syfert, M., Sztyber, A. (eds) Advanced Solutions in Diagnostics and Fault Tolerant Control. DPS 2017. Advances in Intelligent Systems and Computing, vol 635. Springer, Cham. https://doi.org/10.1007/978-3-319-64474-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-64474-5_23

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-64474-5

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