Medical Exam Question Answering with Large-scale Reading Comprehension

Understand

Reading and understanding text is one important component in computer aided diagnosis in clinical medicine, also being a major research problem in the field of NLP.

• In this work, we introduce a question-answering task called MedQA to study answering questions in clinical medicine using knowledge in a large-scale document collection.
• The aim of MedQA is to answer real-world questions with large-scale reading comprehension.
• We propose our solution SeaReader--a modular end-to-end reading comprehension model based on LSTM networks and dual-path attention architecture.