  This paper describes the machine translation systems developed by the
Universidade Federal do Rio Grande do Sul (UFRGS) team for the biomedical
translation shared task. Our systems are based on statistical machine
translation and neural machine translation, using the Moses and OpenNMT
toolkits, respectively. We participated in four translation directions for the
English/Spanish and English/Portuguese language pairs. To create our training
data, we concatenated several parallel corpora, both from in-domain and
out-of-domain sources, as well as terminological resources from UMLS. Our
systems achieved the best BLEU scores according to the official shared task
evaluation.
