A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis.

ABSTRACT: BACKGROUND:With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. OBJECTIVE:This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since

SUBMITTER: Kim S 

PROVIDER: S-EPMC5783222 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature