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Big Health Data Mining

  • Chao Zhang
  • Shunfu Xu
  • Dong Xu
Chapter
Part of the Health Information Science book series (HIS)

Abstract

With the improvement of infrastructures and techniques, “Big Data” provides great opportunities to health informatics, but at the same time raises unparalleled challenges to data scientists. As an interdisciplinary field, the health data are not limited to electronic health record (EHR), as more and more molecular-level data are used for disease diagnosis and prognosis in clinics. Effectively integrating and mining these data holds an indispensable key to translate theoretical models into clinical applications in precision medicine. In this chapter, we briefly demonstrate different data levels involved in health informatics. Then we introduce some general data mining approaches applied to different levels of health data. Finally, a case study is illustrated as an example for applying computational methods on mining long-term EHR data in epidemiological studies.

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Institute for Computational BiomedicineWeill Cornell MedicineNew YorkUSA
  2. 2.Division of Hematology and Medical Oncology, Department of MedicineWeill Cornell MedicineNew YorkUSA
  3. 3.Department of GastroenterologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
  4. 4.Department of Computer Science and C.S. Bond Life Sciences CenterUniversity of MissouriColumbiaUSA

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