AN APPLICATION OF DATA MINING TECHNOLOGY WITH AIM OF DIFFERENTIAL DIAGNOSTICS OF THE COMORBIDIC STATES OF CHRONIC PANCREATITIS AND ASCARIDOSIS ON THE BASIS OF DATA OF CLINICAL SYMPTOMATOLOGY AND ULTRASONIC RESEARCHES

Authors

  • V. P. Martsenyuk University of Bielsko-Biala, Poland http://orcid.org/0000-0001-5622-1038
  • L. S. Babinets SHEI "I. Ya. Gorbachevsky Ternopil state medical university of MH of Ukraine"
  • Yu. V. Dronyak SHEI "I. Ya. Gorbachevsky Ternopil state medical university of MH of Ukraine"

DOI:

https://doi.org/10.11603/mie.1996-1960.2017.4.8447

Keywords:

chronic pancreatitis, ascaridosis, comorbidity, clinical symptomatology, ultrasonic, decision tree, data mining, R, C5.0.

Abstract

For diagnostics of chronic pancreatitis and ascaridosis comorbidity methodology of decision tree construction based on C5.0 algorithm is used. Data of both clinical symptomatology and ultrasonography can be applied. For each of types of researches and also for their totality a separate decision tree is built. The error of algorithm is investigated.

References

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Published

2018-02-20

How to Cite

Martsenyuk, V. P., Babinets, L. S., & Dronyak, Y. V. (2018). AN APPLICATION OF DATA MINING TECHNOLOGY WITH AIM OF DIFFERENTIAL DIAGNOSTICS OF THE COMORBIDIC STATES OF CHRONIC PANCREATITIS AND ASCARIDOSIS ON THE BASIS OF DATA OF CLINICAL SYMPTOMATOLOGY AND ULTRASONIC RESEARCHES. Medical Informatics and Engineering, (4). https://doi.org/10.11603/mie.1996-1960.2017.4.8447

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