Text Classification Model Explainability for Keyword Extraction - Towards Keyword-Based Summarization of Nursing Care Episodes.

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.

Management of Patient Flow in Vascular and Interventional Radiology During MERS-CoV Outbreak.

In 2015, an outbreak of Middle East respiratory syndrome coronavirus occurred in Saudi Arabia and necessitated special measures to be implemented to control the spread of the virus. In this article, we will discuss how the outbreak was managed in the vascular and interventional radiology (VIR) suite in a large tertiary care hospital in Saudi Arabia. Various measures were taken to reduce the risk of transmission of infection. Unit-level education played an important role in the care of patients. A hospital-wide educational program was implemented to ensure zero transmission of infection. Special attention was made to monitor staff who acquired the virus. VIR suite was able to handle the situation and control the outbreak.