Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Large scale modeling of antimicrobial resistance with interpretable
  classifiers   Antimicrobial resistance is an important public health concern that has
implications in the practice of medicine worldwide. Accurately predicting
resistance phenotypes from genome sequences shows great promise in promoting
better use of antimicrobial agents, by determining which antibiotics are likely
to be effective in specific clinical cases. In healthcare, this would allow for
the design of treatment plans tailored for specific individuals, likely
resulting in better clinical outcomes for patients with bacterial infections.
In this work, we present the recent work of Drouin et al. (2016) on using Set
Covering Machines to learn highly interpretable models of antibiotic resistance
and complement it by providing a large scale application of their method to the
entire PATRIC database. We report prediction results for 36 new datasets and
present the Kover AMR platform, a new web-based tool allowing the visualization
and interpretation of the generated models.

12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci