ArticleScientific reports2019
PedMap: a pediatric diseases map generated from clinical big data from Hangzhou, China.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Communicating exploratory unsupervised machine learning analysis in age clustering for paediatric disease.BMJ health & care informatics · 2024Observational
- The influence of the COVID-19 pandemic on the spectrum of neonatal disease in a tertiary hospital in China: A retrospective analysis.Health science reports · 2024Article
- Characteristics and Admission Preferences of Pediatric Emergency Patients and Their Waiting Time Prediction Using Electronic Medical Record Data: Retrospective Comparative Analysis.Journal of medical Internet research · 2023Article
- Systematic exploration of eczema-associated paediatric diseases in a Chinese population of millions: A retrospective observation study.Clinical and translational allergy · 2023Article
- Effects of ambient temperature on outpatient visits for dermatitis in Xinxiang, China: a time-series analysis.Environmental science and pollution research international · 2022Article
- Improvement in childhood cancer survival in Lithuania over three decades.Acta medica Lituanic · 2020Article
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Authors and funding
7 authors.
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Abstract
Epidemiological knowledge of pediatric diseases may improve professionals' understanding of the pathophysiology of and risk factors for diseases and is also crucial for decision making related to workforce and resource planning in pediatric departments. In this study, a pediatric disease epidemiology knowledgebase called PedMap (http://pedmap.nbscn.org) was constructed from the clinical data from 5 447 202 outpatient visits of 2 189 868 unique patients at a children's hospital (Hangzhou, China) from 2013 to 2016. The top 100 most-reported pediatric diseases were identified and visualized. These common pediatric diseases were clustered into 4 age groups and 4 seasons. The prevalence, age distribution and co-occurrence diseases for each disease were also visualized. Furthermore, an online prediction tool based on Gaussian regression models was developed to predict pediatric disease incidence based on weather information. PedMap is the first comprehensive epidemiological resource to show the full view of age-related, seasonal, climate-related variations in and co-occurrence patterns of pediatric diseases.
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