AsthmaKGxE: An asthma–environment interaction knowledge graph leveraging public databases and scientific literature

Asaad, Chaimae; Ghogho, Mounir

doi:10.1016/j.compbiomed.2022.105933

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…The higher prevalence of chronic cough and wheezy in the last 12 months in families with low economic status or low SES may be related to environmental exposures. Studies suggest that families with low SES are more exposed to such factors as indoor allergens, poor housing, and psychosocial stressors resulting from social marginalization, community, or family violence, among others [ 12 , 22 , 23 , 30 ]. The analyses conducted in our study showed that the most common determinant of asthma, bronchitis, wheezing attacks at the night, wheezy in the last 12 months and chronic cough was the presence of mold in children’s apartments.…”

Section: Discussionmentioning

confidence: 99%

Social Inequalities: Do They Matter in Asthma, Bronchitis, and Respiratory Symptoms in Children?

Wypych-Ślusarska

Krupa‐Kotara

Niewiadomska

2022

IJERPH

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Background: Social inequalities (e.g., poverty and low level of education) generate inequalities in health. Aim: The aim of the study was to determine the relationships between indicators of social inequalities and the frequency of respiratory symptoms, asthma, and bronchitis in children. Material and Methods: In 2019, an epidemiological cross-sectional study on 3237 students from elementary schools in Silesia Voivodships (South Poland) was conducted. The students’ parents completed a questionnaire based on the International Study on Asthma and Allergies in Childhood (ISAAC). Social inequalities in the children’s families were determined according to parents’ education and professional status (working vs. unemployed), self-assessment of economic status, and housing conditions. To determine the influence of social factors on the occurrence of asthma, bronchitis, and respiratory symptoms, the odds ratio (OR) was calculated. Results: Children living in apartments with traces of mold had a higher risk of developing asthma (OR = 1.5, 95%CI: 1.17–1.96; p = 0.002) or bronchitis (OR = 1.4, 95%CI: 1.13–1.72; p = 0.002), wheezing attacks at nights (OR = 1.4; 95%CI: 1.01–1.93), wheezy in the last 12 months (OR = 1.6; 95%CI:1.24–2.08; p < 0.001), and chronic cough (OR = 1.9; 95%CI: 1.49–2.46; p < 0.001). Exposure to environmental tobacco smoke (ETS) was associated with higher risk of cough (OR = 1.5 95%CI: 1.22–1.96; p < 0.001) and dyspnea in the last 12 months (OR = 1.4; 95%CI: 1.04–2.00; p = 0.02). Low socioeconomic status (SES) was associated with increased risk of chronic cough (OR = 1.5; 95%CI: 1.09–2.03; p = 0.009) and increased risk of wheezy in the last 12 months (OR = 1.4; 95%CI: 1.06–1.97; p = 0.008). Asthma and bronchitis were not dependent on parents’ education or professional status. Conclusions: Social inequalities have significant impacts on the occurrence of respiratory symptoms, bronchitis, and asthma in children. Interventions aimed at preventing bronchitis and childhood asthma should also focus on social health determinants.

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Section: Discussionmentioning

confidence: 99%

Social Inequalities: Do They Matter in Asthma, Bronchitis, and Respiratory Symptoms in Children?

Wypych-Ślusarska

Krupa‐Kotara

Niewiadomska

2022

IJERPH

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“…Data-driven decisions are made in many industries due to the growing need for the use of data in today's society, which significantly affects people's daily lives [4]. On the other hand, ensemble methods that use decision trees continue to outperform other types of ML on these tabular data [5] [6]. The purpose of decision trees is to build a partial function to classify the data and resolve the problem at hand.…”

Section: Introductionmentioning

confidence: 99%

XBNet and Text Mining-based Genetic Diseases Classification

Abd,

Jassim,

Omri

et al. 2023

Preprint

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Text mining can be used for various biological and medical purposes. In this work, we have used text mining to analyze various papers related to Alzheimer's, Asthma, Cancer, Diabetes, Fabry, and various syndrome diseases using their abstracts and extracting from the text the related gene to those diseases. In this case, the data set collected from the various sources was generated manually in this pilot study. The text was collected from various articles searched through PubMed, Web of Science, and Medline. Extremely Boosted Neural Network is a new machine learning (ML) algorithm that has been developed recently to train a new optimization technique and can integrate tree-based models with Neural networks (NN). In this paper, an extremely boosted neural network was utilized as a novel application for the analysis of text data to extract information about the diseases. We benchmark the proposed model with 17 other ML models, achieving 98% accuracy. This is a significant improvement given that most of the benchmark techniques received less than 97%.

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Relation Extraction

Devarakonda,

Raja,

2024

Cognitive Informatics in Biomedicine and Healthcare

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AsthmaKGxE: An asthma–environment interaction knowledge graph leveraging public databases and scientific literature

Cited by 4 publications

References 19 publications

Social Inequalities: Do They Matter in Asthma, Bronchitis, and Respiratory Symptoms in Children?

Social Inequalities: Do They Matter in Asthma, Bronchitis, and Respiratory Symptoms in Children?

XBNet and Text Mining-based Genetic Diseases Classification

Relation Extraction

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