Applicability of internet search index for asthma admission forecast using machine learning

作者：Luo Li; Liao Chengcheng; Zhang Fengyi^*; Zhang Wei; Li Chunyang; Qiu Zhixin; Huang Debin

来源：International Journal of Health Planning and Management, 2018, 33(3): 723-732.

DOI：10.1002/hpm.2525

• asthma hospitalization
• internet search
• machine learning

ObjectiveThis study aimed to determine whether a search index could provide insight into trends in asthma admission in China. An Internet search index is a powerful tool to monitor and predict epidemic outbreaks. However, whether using an internet search index can significantly improve asthma admissions forecasts remains unknown. The long-term goal is to develop a surveillance system to help early detection and interventions for asthma and to avoid asthma health care resource shortages in advance.
MethodsIn this study, we used a search index combined with air pollution data, weather data, and historical admissions data to forecast asthma admissions using machine learning.
ResultsResults demonstrated that the best area under the curve in the test set that can be achieved is 0.832, using all predictors mentioned earlier.
ConclusionA search index is a powerful predictor in asthma admissions forecast, and a recent search index can reflect current asthma admissions with a lag-effect to a certain extent. The addition of a real-time, easily accessible search index improves forecasting capabilities and demonstrates the predictive potential of search index.

• 出版日期2018-9
• 单位四川大学