Abstract
In this study, we first make a comprehensive literature review about the role of big data in healthcare industry, and the application of big data in demand forecasting. After that, we collect data from search engine and company to generate medical device demand forecasting approach. Then, we compare the proposed approach will univariate demand forecasting approaches. We find that search engine is a powerful way for patients to know the basic information about disease and the data are significantly correlated with the demand of medical devices. By introducing the big data into the forecasting model, the forecasting accuracy can be further improved. Therefore, we contribute to the knowledge by analyzing the role of bid data in healthcare supply chain. We also build a machine learning approach using search engine data to forecast the demand of medical device.
Original language | English |
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Pages (from-to) | 32-39 |
Number of pages | 8 |
Journal | Procedia Manufacturing |
Volume | 39 |
DOIs | |
Publication status | Published - 2019 |
Event | 25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019 - Chicago, United States Duration: 9 Aug 2019 → 14 Aug 2019 |
Keywords
- Big data
- Forecasting
- Machine learning
- Medical device
- Time series
ASJC Scopus subject areas
- Artificial Intelligence
- Industrial and Manufacturing Engineering