Study on the Automatic Recommendation Method for Answer Analysis of Pediatric Medical Examination Questions
10.3969/j.issn.1673-6036.2024.10.003
- VernacularTitle:面向儿科医学试题的答案解析自动推荐方法研究
- Author:
Juan WANG
1
;
Li HOU
;
Yueping SUN
;
Jiaming LI
;
Li YANG
;
Liangguang DONG
;
Yunhan LI
Author Information
1. 中国医学科学院/北京协和医学院医学信息研究所 北京 100020
- Keywords:
medical test questions;
answer analysis;
latent semantic indexing(LSI);
MC-BERT;
CoSENT;
natural language pro-cessing(NLP)
- From:
Journal of Medical Informatics
2024;45(10):11-17
- CountryChina
- Language:Chinese
-
Abstract:
Purpose/Significance To explore and implement the automated interpretation of pediatric medical exam answers,so as to enhance the efficiency and quality of answer explanation compilation.Method/Process The paper proposes a method that combines latent semantic indexing(LSI),MC-BERT,and the CoSENT model.Initially,multiple candidate answer explanations are extracted from ref-erence documents using the LSI method and the MC-BERT model.Subsequently,the CoSENT model is employed to calculate the simi-larity between the candidate explanations and the question stems as well as the answer options.The candidate explanation with the highest similarity is then selected as the final answer explanation.Result/Conclusion The experimental results show that the method presented in this paper achieves a precision rate of 72.6％.Compared to single methods or models,it significantly improves the recall and precision of answer parsing,effectively enhances the efficiency of compiling question answer explanations,reduces the burden on educators,and pro-vides significant data support for educational research.
