Vladimir Ivančević1, Ivan Tušek2, Jasmina Tušek3, Marko Knežević4, Salaheddin Elheshk4, Ivan Luković4. 1. University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21 000 Novi Sad, Serbia. Electronic address: dragoman@uns.ac.rs. 2. University of Novi Sad, Medical Faculty, Hajduk Veljkova 3, 21 000 Novi Sad, Serbia. 3. Private Dental Office Palmadent, Mažuranićeva 4, 21 131 Petrovaradin, Serbia. 4. University of Novi Sad, Faculty of Technical Sciences, Trg Dositeja Obradovića 6, 21 000 Novi Sad, Serbia.
Abstract
BACKGROUND AND OBJECTIVE: Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. METHODS: ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Bačka area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. RESULTS: Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. CONCLUSIONS: The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods.
BACKGROUND AND OBJECTIVE: Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. METHODS: ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Bačka area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. RESULTS: Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. CONCLUSIONS: The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods.
Authors: Rosana Veroneze; Sâmia Cruz Tfaile Corbi; Bárbara Roque da Silva; Cristiane de S Rocha; Cláudia V Maurer-Morelli; Silvana Regina Perez Orrico; Joni A Cirelli; Fernando J Von Zuben; Raquel Mantuaneli Scarel-Caminaga Journal: PLoS One Date: 2020-10-02 Impact factor: 3.240