Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29226, first published .
Predicting Antituberculosis Drug–Induced Liver Injury Using an Interpretable Machine Learning Method: Model Development and Validation Study

Predicting Antituberculosis Drug–Induced Liver Injury Using an Interpretable Machine Learning Method: Model Development and Validation Study

Predicting Antituberculosis Drug–Induced Liver Injury Using an Interpretable Machine Learning Method: Model Development and Validation Study

Tao Zhong 1*, BSc;  Zian Zhuang 2, 3, 4*, BSc;  Xiaoli Dong 5, 6, PhD;  Ka Hing Wong 5, 6, PhD;  Wing Tak Wong 5, 6, PhD;  Jian Wang 1, BSc;  Daihai He 2, 4, PhD;  Shengyuan Liu 1, PhD

1 Department of Tuberculosis Control, Shenzhen Nanshan Center for Chronic Disease Control , Shenzhen , CN

2 Department of Applied Mathematics, The Hong Kong Polytechnic University , Hong Kong , CN

3 Department of Biostatistics, University of California , Los Angeles, CA, US

4 Hong Kong Polytechnic University Shenzhen Research Institute , Shenzhen , CN

5 Research Institute for Future Food, The Hong Kong Polytechnic University , Hong Kong , CN

6 Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University , Hong Kong , CN

*these authors contributed equally

Corresponding Author:

  • Shengyuan Liu, PhD
  • Department of Tuberculosis Control
  • Shenzhen Nanshan Center for Chronic Disease Control
  • Hua Ming Road No 7
  • Nanshan District
  • Shenzhen
  • CN
  • Phone: 86 13543301395
  • Email: jfk@sznsmby.com