An AutoML Approach for Predicting Risk of Progression to Active Tuberculosis based on Its Association with Host Genetic Variations

Wanying Dou, Yihang Liu, Zehai Liu, Dauren Yerezhepov, Ulan Kozhamkulov, Ainur Akilzhanova, Omar Dib, Chee-Kai Chan. An AutoML Approach for Predicting Risk of Progression to Active Tuberculosis based on Its Association with Host Genetic Variations. In ICBBS 2021: 10th International Conference on Bioinformatics and Biomedical Science, Xiamen, China, October 29 - 31, 2021. pages 82-88, ACM, 2021. [doi]

@inproceedings{DouLLYKADC21,
  title = {An AutoML Approach for Predicting Risk of Progression to Active Tuberculosis based on Its Association with Host Genetic Variations},
  author = {Wanying Dou and Yihang Liu and Zehai Liu and Dauren Yerezhepov and Ulan Kozhamkulov and Ainur Akilzhanova and Omar Dib and Chee-Kai Chan},
  year = {2021},
  doi = {10.1145/3498731.3498743},
  url = {https://doi.org/10.1145/3498731.3498743},
  researchr = {https://researchr.org/publication/DouLLYKADC21},
  cites = {0},
  citedby = {0},
  pages = {82-88},
  booktitle = {ICBBS 2021: 10th International Conference on Bioinformatics and Biomedical Science, Xiamen, China, October 29 - 31, 2021},
  publisher = {ACM},
  isbn = {978-1-4503-8430-8},
}