Exploring Common Symptoms in Patients with Respiratory Allergies Using K-Means Algorithm in the North-East of Iran in 2012-2015.

Q3 Medicine
Tanaffos Pub Date : 2023-01-01
Somaye Norouzi, Samane Sistani, Maryam Khoshkhui, Reza Faridhosseini, Payam Payandeh, Fahimeh Ghasemian, Leila Ahmadian, Mohammadhossein Pourasad, Farahzad Jabbari Azad
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Abstract

Background: As a common disease among people of almost any age, allergic rhinitis has many adverse effects such as lowering the quality of life and efficiency at work or school. Considering these conditions and the collection of large amounts of data, the present research was conducted on allergic rhinitis and asthma patients' data to extract the common symptoms of these diseases using cluster analysis and the k-means algorithm.

Materials and methods: The present cross-sectional research was conducted in Mashhad city. The inclusion criteria were affliction with one or two respiratory allergy diseases diagnosed by an allergy specialist through clinical history taking and physical examination. A researcher-made checklist was used in the present study for data collection. Then, the K-means algorithm's cluster analysis model was conducted to extract clusters (WEKA software (3, 6, 9)).

Results: Overall, 1,231 patients met the inclusion criteria. The result of the Cluster analysis consisted of Cluster 1 in allergic rhinitis consisted of 702 patients, and cluster 2 consisted of 382 patients.46 asthma patients were assigned to cluster 1 and 23 to cluster 2.Also, 60 asthma and allergic rhinitis patients were assigned to cluster 1 and 19 to cluster 2. The most common symptoms in all patients were rhinorrhea, sneezing, nasal congestion, and itchy nose.

Conclusion: Overall, Salsola kali was the most common allergen in allergic rhinitis and asthma patients. Also, the most common symptoms in patients are rhinorrhea, sneezing, itchy nose, and nasal congestion. This study can help physicians diagnose allergic rhinitis and asthma in geographical areas with a high prevalence of Salsola kali.

Abstract Image

2012-2015年在伊朗东北部使用K-Means算法探索呼吸道过敏患者的常见症状。
背景:过敏性鼻炎是几乎任何年龄段人群的常见疾病,有许多不良影响,如降低工作或学校的生活质量和效率。考虑到这些情况和大量数据的收集,本研究对过敏性鼻炎和哮喘患者的数据进行了研究,使用聚类分析和k-means算法提取这些疾病的常见症状。材料和方法:本研究在马什哈德市进行。纳入标准是过敏专家通过临床病史和体检诊断出的一种或两种呼吸道过敏疾病。本研究采用研究人员编制的检查表进行数据收集。然后,使用K-means算法的聚类分析模型(WEKA软件(3,6,9))提取聚类。结果:总体而言,1231名患者符合纳入标准。聚类分析的结果包括过敏性鼻炎的聚类1,由702名患者组成,聚类2由382名患者组成。46名哮喘患者被分配到聚类1,23名被分配到分组2。此外,60名哮喘和过敏性鼻炎患者被分配至聚类1,19名被分配至分组2。所有患者最常见的症状是鼻漏、打喷嚏、鼻塞和鼻子发痒。结论:总的来说,碱蓬是过敏性鼻炎和哮喘患者最常见的过敏原。此外,患者最常见的症状是鼻漏、打喷嚏、鼻子发痒和鼻塞。这项研究可以帮助医生诊断过敏性鼻炎和哮喘高发病率的地理区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Tanaffos
Tanaffos Medicine-Critical Care and Intensive Care Medicine
CiteScore
1.10
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