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QIAO JIN | 金乔

PhD STUDENT IN GROUPLENS

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Diabetes Disease Risk Prediction Based on Machine Learning

Diabetes Disease Risk Prediction Based on Machine Learning
Dec. 2017 – Mar. 2018
Tag: Machine learning, Health Monitoring,Xgboost, Python

Chronic diseases such as cardiovascular diseases and diabetes account for 80% of the total deaths annually, and the annual expenditure on chronic diseases accounts for more than 13% of China’s public health expenditure. As a common chronic disease, diabetes mellitus can not be cured at present, but it’s incidence can be reduced through scientific and effective prevention and treatment.

In this project, I

  • Designed and applied Xgboost to predict diabetes disease risk with features including albumin, cholesterol, etc. Optimized the GBDT to reach higher precision(f1score 0.7).
  • Participated into the overall diabetes disease risk prototype system implementation in Python.

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Contact

georgiejin0628@gmail.com
jin00122@umn.edu

Grouplens Research Center,
University of Minnesota,
Minneapolis, MN, US

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