What question did this study set out to answer?

The aim is to create a dataset that facilitates the answering of biomedical research questions using natural language processing techniques.

January 1, 2019Open Access

PubMedQA: A Dataset for Biomedical Research Question Answering

Key Points

The aim is to create a dataset that facilitates the answering of biomedical research questions using natural language processing techniques.
Developed a novel dataset for biomedical research question answering.
Utilized natural language processing techniques for dataset construction and evaluation.
Presented findings at the EMNLP-IJCNLP 2019 conference.
Introduced a comprehensive dataset designed for improving question answering in the biomedical domain.
Demonstrated the use of advanced NLP methods for generating and validating the dataset.

Abstract

Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, Xinghua Lu. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Bookmark

View Full Paper

Cite This Study

Jin et al. (Tue,) studied this question.

synapsesocial.com/papers/69dc6a05cdb4abb1d71333e1 https://doi.org/https://doi.org/10.18653/v1/d19-1259

Also Consider

Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context:

Bookmark

View Full Paper