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Objectives@#Low birth weight (LBW) is a global concern associated with fetal and neonatal mortality as well as adverse consequences such as intellectual disability, impaired cognitive development, and chronic diseases in adulthood. Numerous factors contribute to LBW and vary based on the region. The main objectives of this study were to compare four machine learning classifiers in the prediction of LBW and to determine the most important factors related to this phenomenon in Hamadan, Iran. @*Methods@#We carried out a retrospective cross-sectional study on a dataset collected from Fatemieh Hospital in 2017 that included 741 mother-newborn pairs and 13 potential factors. Decision tree, random forest, artificial neural network, support vector machine, and logistic regression (LR) methods were used to predict LBW, with five evaluation criteria utilized to compare performance. @*Results@#Our findings revealed a 7% prevalence of LBW. The average accuracy of all models was 87% or higher. The LR method provided a sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and accuracy of 74%, 89%, 7.04%, 29%, and 88%, respectively. Using LR, gestational age, number of abortions, gravida, consanguinity, maternal age at delivery, and neonatal sex were determined to be the six most important variables associated with LBW. @*Conclusions@#Our findings underscore the importance of facilitating timely diagnosis of causes of abortion, providing genetic counseling to consanguineous couples, and strengthening care before and during pregnancy (particularly for young mothers) to reduce LBW.
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Introduction and Aims: Brucellosis is an important disease caused by Brucella species and is a zoonotic disease. Since Iran has focused the majority of livestock in rural areas, the epidemiological studies seems to be necessary in cities with most villages. We aim to survey the brucellosis in suspicious patients who referred to a medical diagnostic laboratory in Neyshabur from 2010 to 2015
Materials and Methods: This study was cross sectional-descriptive. In this epidemiological study, the required information of all patients who were suspected by physicians [2010-2015] was extracted over the last 5 years by laboratory software and the collected data were analyzed by using SPSS
Results: According to Wright's test, the prevalence of brucellosis was 6.76% in this study. Patients had the titers of 1.80, 1.40 and 1.40 for Wright, 2-Mercapto ethanol [2ME] and Coombs tests respectively. Most participants were in the age group of 41-50 years and 34.1% were male
Conclusions: According to results, Neyshabur has categorized in the areas with high outbreak in the country that should be considered as priorities of local health networks for training and necessary acts