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Disease Prediction Based on Transfer Learning in Individual Healthcare

  • Yang Song
  • Tianbai Yue
  • Hongzhi WangEmail author
  • Jianzhong Li
  • Hong Gao
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 727)

Abstract

Nowadays, emerging mobile medical technology and disease prevention become new trends of disease prevention and control. Based on this technology, we present disease prediction models based on transfer learning. Breast cancer disease data has been used to build our model. According to the neural networks, the basic model has been provided. With unlabeled data, transfer learning is a appropriate way to revise the module to increase accuracy. The test results show that the algorithm is suitable for data classification, especially for unlabeled health data.

Keywords

Individual healthcare Transfer learning Neural networks Disease prediction Unlabeled data 

Notes

Acknowledgments

This paper was partially supported by National Sci-Tech Support Plan 2015BAH10F01, NSFC grant U1509216,61472099, the Scientific Research Foundation for the Returned Overseas Chinese Scholars of Heilongjiang Province LC2016026 and MOE-Microsoft Key Laboratory of Natural Language Processing and Speech, Harbin Institute of Technology.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Yang Song
    • 1
  • Tianbai Yue
    • 2
  • Hongzhi Wang
    • 1
    Email author
  • Jianzhong Li
    • 1
  • Hong Gao
    • 1
  1. 1.Massive Data Computing Research CenterHarbin Institute of TechnologyHarbinChina
  2. 2.Heilongjiang UniversityHarbinChina

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