We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations.  Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis.  synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs.  Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.
synVep
Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). 
gnomAD