Best model for Antimicrobial Resistance (AMR) prediction?

Some classes of problem are best solved by a specific class of machine learning model, due to the structure of the data (e.g. CNN's for computer vision tasks).

Prediction of bacterial resistance/susceptibility to antimicrobials (from genotypic data) using Machine Learning methods is a problem that has started receiving interest in recent years.

The following paper (from 2017) analysed the then current literature and found that:

To date, there has not been a consensus about the optimal machine learning model to be used for AST genotype–phenotype prediction, as reflected by the diverse algorithms authors have implemented (Table 1).

• Machine learning: novel bioinformatics approaches for combating antimicrobial resistance
  
  Macesica, Polubriaginof, Tatonettib (2017)

Has this changed in the past 2 years?

Is there now a consensus about which models are most effective?

^{References: Table 1 from paper:}