Drug resistance classification for Mycobacterium tuberculosis using multi-output model with stacked auto-encoders
This work explores deep-learning model to classify drug resistance for Mycobacterium tuberculosis. We applied an end-to-end model on DNA mutations of the pathogen and lab-based phenotyping results. The model first stacks 3 auto-encoders, and then applies multiple classifiers to classify resistance f...
| Egile Nagusiak: | , |
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| Formatua: | Conference item |
| Argitaratua: |
Institute of Electrical and Electronics Engineers
2017
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