Paper Info
Title
Htl Model: A Model For Extracting And Visualizing Medical Events From Narrative Text In Electronic Health Records
Abstract
Electronic health records contain important information of a patient and it may serve as source to analyze and audit the process of diagnosis and treatment of a specific clinical condition. This information is registered in narrative text, which generates a limitation to identify medical events like doctor appointments, medications, treatments, surgical procedures, etc. As it is difficult to identify medical events in electronic health records, it is not easy to find a point of comparison between this electronic information with recommendations given by clinical practice guidelines. Such guides correspond to recommendations systematically developed to assist health professionals in taking appropriate decisions with respect to illness. This article presents "Health Text Line Model HTL", a model for extraction, structuring and viewing medical events from narrative text in electronic health records. The HTL model was implemented in a framework that integrates the aforementioned processes to identify and timing medical events. HTL was validated in a general hospital giving good results on precision and recall.
Year
DOI
Venue
2016
10.5220/0005863501070114
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES FOR AGEING WELL AND E-HEALTH (ICT4AWE)
Keywords
Field
DocType
Text Mining, Clinical Practice Guidelines, Medical Events, Temporal Expressions, Electronic Health Records
World Wide Web,Information retrieval,Computer science,Narrative
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Eddie Paul Hernández100.34
Alexandra Pomares2108.69
Oscar Mauricio Muñoz310.69