Comparison between statistical and fuzzy approaches for improving diagnostic decision making in patients with chronic nasal symptoms

Valerio Lacagnina, Gabriele Di Lorenzo, Maria Stefania Leto Barone, Giuseppe Pingitore, Giuseppe Pingitore, Giuseppe Pingitore, Simona La Piana

Risultato della ricerca: Articlepeer review

5 Citazioni (Scopus)

Abstract

This paper compares a fuzzy model, expressed in rule-form, with a well known statistical approach (i.e. logistic regressionmodel) for diagnostic decision making in patients with chronic nasal symptoms. The analyses were carried out using a database obtained from a questionnaire administered to 1359 patients with nasal symptoms containing personal data, clinical data and skin prick test (SPT) results. Both the fuzzy model and the logistic regression model developed were validated using a data set obtainedfrom another medical institution. The accuracy of the two models in identifying patients with positive or negative SPT was similar.This study is a preliminary step to the creation of a software that primary care doctors can use to make a diagnostic decision, when deciding whether patients with nasal symptoms need allergy testing or not.
Lingua originaleEnglish
pagine (da-a)136-150
Numero di pagine15
RivistaFuzzy Sets and Systems
Volume237
Stato di pubblicazionePublished - 2013

All Science Journal Classification (ASJC) codes

  • Logic
  • Artificial Intelligence

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