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Article

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Title

Can AI Help Pediatricians? Diagnosing Kawasaki Disease Using DRSA

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki, Politechnika Poznańska | [ 2 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2021

Published in

Children

Journal year: 2021 | Journal volume: vol. 8 | Journal number: iss. 10

Article type

scientific article

Publication language

english

Keywords
EN
  • Kawasaki disease
  • infectious mononucleosis
  • Streptococcus pyogenes
  • children
  • DRSA
  • differential diagnosis
Abstract

EN The DRSA method (dominance-based rough set approach) was used to create decision-making rules based on the results of physical examination and additional laboratory tests in the differential diagnosis of Kawasaki disease (KD), infectious mononucleosis and S. pyogenes pharyngitis in children. The study was conducted retrospectively. The search was based on the ICD-10 (International Classification of Diseases) codes of final diagnosis. Demographic and laboratory data from one Polish hospital (Poznan) were collected. Traditional statistical methods and the DRSA method were applied in data analysis. The algorithm formed 45 decision rules recognizing KD. The rules with the highest sensitivity (number of false negatives equals zero) were based on the presence of conjunctivitis and CRP (C-reactive Protein) ≥ 40.1 mg/L, thrombocytosis and ESR (Erythrocyte Sedimentation Rate) ≥ 77 mm/h; fair general condition and fever ≥ 5 days and rash; fair general condition and fever ≥ 5 days and conjunctivitis; fever ≥ 5 days and rash and CRP ≥ 7.05 mg/L. The DRSA analysis may be helpful in diagnosing KD at an early stage of the disease. It can be used even with a small amount of clinical or laboratory data.

Date of online publication

17.10.2021

Pages (from - to)

929-1 - 929-9

DOI

10.3390/children8100929

URL

https://www.mdpi.com/2227-9067/8/10/929

Comments

Article Number: 929

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

40

Ministry points / journal in years 2017-2021

40

Impact Factor

2,835

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