Detection of Muscle Weakness in Medical Texts Using Natural Language Processing
DIGITAL PERSONALIZED HEALTH AND MEDICINE(2020)
Abstract
Identifying adverse events in clinical documents is demanded in retrospective clinical research and prospective monitoring of treatment safety and cost-effectiveness. We proposed and evaluated a few methods of semi-automated muscle weakness detection in preoperative clinical notes for a larger project on predicting paresis by images. The combination of semi-expert and machine learning methods demonstrated maximized sensitivity = 0.860 and specificity = 0.919, and largest AUC = 0.943 with a 95% CI [0.874; 0.991], outperforming each method used individually. Our approaches are expected to be effective for autoshaping a well-verified training dataset for supervised machine learning.
MoreTranslated text
Key words
Electronic Health Records,Neurosurgery,Natural Language Processing,Adverse Events,Logistic Regression,ROC-analysis
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined