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Analysis of health patterns in Yazd teachers: application of data mining clustering for physical and clinical indicators Abstract
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Hamed Fallah Tafti   , Saeede Rastjoo , Batool Zeidabadi , Somayeh Kargar |
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Abstract: (104 Views) |
| The healthcare industry is directly generating a large amount of data, and those who encounter this type of data have found that there is a wide gap between its collection and interpretation. The main objective of this research is to cluster teachers based on physical and clinical health indicators using data mining methods.The research is descriptive, exploratory and applied. The data were collected from health centers and the Ministry of Education of Yazd province from May 1398 to May 1400. In this study, 626 cases of the results of physical and clinical health indicators of teachers in Yazd province were used, which include 29 features. Descriptive statistics and data mining methods were used to analyze the information. The Python programming language was used in this project. The results of the study showed that the best clustering method is KMeans with 3 clusters. The silhouette and elbow indices were used to select the best clustering method and the number of clusters, respectively. Finally, the characteristics of each of these three clusters were identified, which can be used to obtain the cluster of new samples based on them.This study showed that data mining methods can be used to identify patterns and trends in data related to teacher health. This information can be useful for better planning of health programs and disease prevention in teachers |
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| Keywords: Clustering, Teachers, Physical and Clinical Health Indicators, Data Mining Methods |
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Type of Study: Research |
Received: 1400/01/09 | Accepted: 1400/01/09 | Published: 1400/01/09
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