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PedMap: a pediatric diseases map generated from clinical big data from Hangzhou, China
Haomin Li1, Gang Yu2, Cong Dong3
1The Children's Hospital of Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou, China. hmli@zju.edu.cn.
Scientific Reports
|November 30, 2019
Summary
This study introduces PedMap, a pediatric disease knowledgebase detailing common illnesses, their age and seasonal patterns, and co-occurrence. It also includes a tool to predict disease incidence using weather data.
Area of Science:
- Pediatric epidemiology
- Clinical informatics
- Public health
Background:
- Understanding pediatric disease epidemiology is vital for clinical insights and resource planning.
- Existing epidemiological data often lacks comprehensive views of disease variations.
Purpose of the Study:
- To construct a comprehensive epidemiological knowledgebase for pediatric diseases (PedMap).
- To identify and visualize patterns in pediatric diseases related to age, season, and climate.
- To develop a predictive tool for pediatric disease incidence.
Main Methods:
- Utilized clinical data from over 5.4 million outpatient visits (2013-2016).
- Identified and visualized the top 100 most-reported pediatric diseases.
- Clustered diseases by age and season, analyzing prevalence, distribution, and co-occurrence.
- Developed a Gaussian regression model for weather-based incidence prediction.
Main Results:
- The PedMap knowledgebase was established, featuring visualized data on pediatric diseases.
- Identified age-related, seasonal, and co-occurrence patterns for common pediatric conditions.
- An online prediction tool linking weather data to disease incidence was created.
Conclusions:
- PedMap is the first resource to offer a holistic view of pediatric disease variations.
- The knowledgebase supports improved understanding of disease pathophysiology and risk factors.
- PedMap aids in strategic planning for pediatric healthcare services.
