Drug resistance classification for Mycobacterium tuberculosis using multi-output model with stacked auto-encoders - Yang, Y; Clifton, D (Institute of Electrical and Electronics Engineers, 2017)
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 for four first-line drugs. The results is promising and show the potential of the model for drug resistance analysis.