Research on Identification of Medical Breakthrough Papers from the Perspective of Abstract Language

Corresponding author: TANG Xiaoli, tang.xiaoli@imicams.ac.cn

DOI: 10.12201/bmr.202305.00013

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  Abstract: Purpose/Significance This paper analyzes the linguistic features of abstracts and explores the method of identifying potential breakthrough papers using abstract text, which provides reference for early discovery of breakthrough papers. Method/Process A representative collection of breakthrough papers is selected, and the characteristic sentence patterns are extracted and the abstract moves are divided. Thus, an abstract recognition model for medical breakthrough papers is constructed using in-depth learning algorithm. Result/Conclusion The model constructed with the objective, conclusion move and feature sentence has good recognition ability, with F1 value of 0.835 1. The empirical results show that the model is applicable in specific medical fields.

  Key words: Breakthrough Papers; Abstract Text; Linguistic Features; Automatic Recognition

  Submit time: 17 May 2023

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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  1	2023-03-06	bmr.202305.00013V1	Download

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