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Image-Centric Integrated Data Model of Medical Information by Diseases: Two Case Studies for AMI and Ischemic Stroke
Author(s) -
Meeyeon Lee,
Ye-Seul Park,
Jungwon Lee
Publication year - 2016
Publication title -
journal of information processing systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.288
H-Index - 23
eISSN - 2092-805X
pISSN - 1976-913X
DOI - 10.3745/jips.04.0027
Subject(s) - computer science , information model , ischemic stroke , stroke (engine) , data model (gis) , data mining , data science , artificial intelligence , medicine , software engineering , ischemia , cardiology , mechanical engineering , engineering
In the medical fields, many efforts have been made to develop and improve Hospital Information System (HIS) including Electronic Medical Record (EMR), Order Communication System (OCS), and Picture Archiving and Communication System (PACS). However, materials generated and used in medical fields have various types and forms. The current HISs separately store and manage them by different systems, even though they relate to each other and contain redundant data. These systems are not helpful particularly in emergency where medical experts cannot check all of clinical materials in the golden time. Therefore, in this paper, we propose a process to build an integrated data model for medical information currently stored in various HISs. The proposed data model integrates vast information by focusing on medical images since they are most important materials for the diagnosis and treatment. Moreover, the model is disease-specific to consider that medical information and clinical materials including images are different by diseases. Two case studies show the feasibility and the usefulness of our proposed data model by building models about two diseases, acute myocardial infarction (AMI) and ischemic stroke.

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