Abstract
Tools to automate the summarization of nursing entries in electronic health records (EHR) have the potential to support healthcare professionals to obtain a rapid overview of a patient's situation when time is limited. This study explores a keyword-based text summarization method for the nursing text that is based on machine learning model explainability for text classification models. This study aims to extract keywords and phrases that provide an intuitive overview of the content in multiple nursing entries in EHRs written during individual patients' care episodes. The proposed keyword extraction method is used to generate keyword summaries from 40 patients' care episodes and its performance is compared to a baseline method based on word embeddings combined with the PageRank method. The two methods were assessed with manual evaluation by three domain experts. The results indicate that it is possible to generate representative keyword summaries from nursing entries in EHRs and our method outperformed the baseline method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
