Forecasting medical device demand with online search queries: A big data and machine learning approach

Shuojiang Xu, Hing Kai Chan

Research output: Journal PublicationConference articlepeer-review

6 Citations (Scopus)

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 languageEnglish
Pages (from-to)32-39
Number of pages8
JournalProcedia Manufacturing
Volume39
DOIs
Publication statusPublished - 2019
Event25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019 - Chicago, United States
Duration: 9 Aug 201914 Aug 2019

Keywords

  • Big data
  • Forecasting
  • Machine learning
  • Medical device
  • Time series

ASJC Scopus subject areas

  • Artificial Intelligence
  • Industrial and Manufacturing Engineering

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