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Extracting Clinical Scale Information and Identifying Trial Cohorts with Semantic Alignment |
Yang Lin,Huang Xiaoshuo,Wang Jiayang,Li Jiao() |
Institute of Medical Information/Medical Library, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100020, China |
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Abstract [Objective] This study develops a method to extract clinical scale information based on semantic alignment, aiming to identify the potential cohort and improve the data-driven clinical research. [Methods] First, we analyzed the features of National Institutes of Health Stroke Scale (NIHSS) with clinical trials and real-world electronic medical records. Then, we proposed an extraction method for clinical scale information based on semantic alignment. Finally, we examined our model with data from ClinicalTrials.gov and open electronic medical record dataset MIMIC-III. [Results] The F1 values of the NIHSS total score and item scores of the extracted contents were 0.953 5 and 0.926 7. We identified patients who met NIHSS criteria effectively. [Limitations] More research is needed to examine this method with other clinical scales and real-world trial recuriment scenario. [Conclusions] The proposed method could effectively address the issue of semantic consistency facing clinical scale information.
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Received: 27 September 2020
Published: 25 December 2020
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Corresponding Authors:
Li Jiao
E-mail: li.jiao@imicams.ac.cn
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