Automated Question Answer medical model based on Deep Learning Technology. (arXiv:2005.10416v1 [cs.CL])

Artificial intelligence can now provide more solutions for different
problems, especially in the medical field. One of those problems the lack of
answers to any given medical/health-related question. The Internet is full of
forums that allow people to ask some specific questions and get great answers
for them. Nevertheless, browsing these questions in order to locate one similar
to your own, also finding a satisfactory answer is a difficult and
time-consuming task. This research will introduce a solution to this problem by
automating the process of generating qualified answers to these questions and
creating a kind of digital doctor. Furthermore, this research will train an
end-to-end model using the framework of RNN and the encoder-decoder to generate
sensible and useful answers to a small set of medical/health issues. The
proposed model was trained and evaluated using data from various online
services, such as WebMD, HealthTap, eHealthForums, and iCliniq.

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