Healthcare data integration using machine learning: A case study evaluation with health information-seeking behavior databases.

Journal: Research in social & administrative pharmacy : RSAP
PMID: 35965198

Abstract

BACKGROUND: The amount of data in health care is rapidly rising, leading to multiple datasets generated for any given individual. Data integration involves mapping variables in different datasets together to form a combined dataset which can then be used to conduct different types of analyses. However, with increasing numbers of variables, manual mapping of a dataset can become inefficient. Another approach is to use text classification through machine learning to classify the variables to a schema.

Authors

  • Ardalan Mirzaei
    The University of Sydney School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, NSW, Australia. Electronic address: ardalan.mirzaei@sydney.edu.au.
  • Parisa Aslani
    The University of Sydney School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, NSW, Australia.
  • Carl R Schneider
    The University of Sydney School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, NSW, Australia.

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