Published
2024-12-02
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Original Research Article
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Copyright (c) 2024 Xiu Lin, Shih-Pin Lee
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How to Cite
The prediction of urinary calculi is conducted using RGIS (regional geographic information system)
Xiu Lin
PhD candidate, Department of Public Health, International College, Krirk University, Bangkok,10220, Thailand
Shih-Pin Lee
Professor, Department of Public Health, International College, Krirk University, Bangkok,10220, Thailand
DOI: https://doi.org/10.59429/ace.v7i3.5566
Abstract
Urolithiasis, a prevalent disorder of the urogenital system, was documented 7000 years ago as a formidable ailment; however, it continues to pose a significant challenge in contemporary medical science. There has been a gradual rise in the prevalence and incidence of lithiasis, with a substantial proportion of young individuals experiencing their initial episode during their twenties and thirties. In general, the prevalence of urinary stones is higher in southern regions compared to northern regions. Since the 1970s, statistical data on the prevalence of urinary stones has consistently indicated a significant regional disparity among patients in China. However, comprehensive epidemiological data on lithiasis at a large scale remains limited. The majority of incidence data has been derived from cross-sectional surveys or admission rates recorded at district hospitals. The study highlights RGIS's (Regional Geographic Information System) role in predicting urolithiasis and analyzing its spatial distribution. It reviews past research on urolithiasis prediction and the use of GIS in healthcare, focusing on RGIS's potential significance. The methodology details data collection, preprocessing, and the development of the RGIS prediction model, along with evaluation metrics. Results show the RGIS model's advantages over others and discuss the disease's spatial patterns. The discussion interprets findings, considering RGIS's limitations, and their implications for public health, stressing the need for targeted interventions in high-risk areas. In conclusion, the study indicates RGIS's potential for predicting urolithiasis and influencing health policies, while recommending further research to overcome current limitations and explore broader applications.
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