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Using Classification and Visualization to Support Clinical Texts Review in Electronic Clinical Documentation by Jonah Kipchirchir Kenei; Elisha Opiyo is a scholarly article available to read on EtoBox.

What is Using Classification and Visualization to Support Clinical Texts Review in Electronic Clinical Documentation about?

Electronic health records, as a repository, of patient information, is nowadays the most commonly used technology to record , store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by lack of clear structure. Therefore, medical practice is facing a challenge thanks to rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient and there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential

Author

Jonah Kipchirchir Kenei; Elisha Opiyo

Publisher

ACM

Published

2022

Language

EN