  This paper describes our competing system to enter the MEDIQA-2019
competition. We use a multi-source transfer learning approach to transfer the
knowledge from MT-DNN and SciBERT to natural language understanding tasks in
the medical domain. For transfer learning fine-tuning, we use multi-task
learning on NLI, RQE and QA tasks on general and medical domains to improve
performance. The proposed methods are proved effective for natural language
understanding in the medical domain, and we rank the first place on the QA
task.
