Visualizing Patient Journals by Combining Vital Signs Monitoring and Natural Language Processing

Adnan Vilic, John Asger Petersen, Karsten Hoppe, Helge Bjarup Dissing Sørensen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper presents a data-driven approach to graphically presenting text-based patient journals while still maintaining all textual information. The system first creates a timeline representation of a patients’ physiological condition during an admission, which is assessed by electronically monitoring vital signs and then combining these into Early Warning Scores (EWS). Hereafter, techniques from Natural Language Processing (NLP) are applied on the existing patient journal to extract all entries. Finally, the two methods are combined into an interactive timeline featuring the ability to see drastic changes in the patients’ health, and thereby enabling staff to see where in the journal critical events have taken place.
Original languageEnglish
Title of host publicationProceedings of 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PublisherIEEE
Publication date2016
Pages2529-2532
Article numberWeCT16.6
ISBN (Print)978-1-4577-0220-4
Publication statusPublished - 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16) - Orlando, FL, United States
Duration: 16 Aug 201620 Aug 2016
Conference number: 38
http://embc.embs.org/2016/

Conference

Conference38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16)
Number38
CountryUnited States
CityOrlando, FL
Period16/08/201620/08/2016
Internet address

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