Title
iT2DMS: a Standard-Based Diabetic Disease Data Repository and its Pilot Experiment on Diabetic Retinopathy Phenotyping and Examination Results Integration.
Abstract
Type 2 diabetes mellitus (T2DM) is a common chronic disease, and the fragment data collected through separated vendors makes continuous management of DM patients difficult. The lack of standard of fragment data from those diabetic patients also makes the further potential phenotyping based on the diabetic data difficult. Traditional T2DM data repository only supports data collection from T2DM patients, lack of phenotyping ability and relied on standalone database design, limiting the secondary usage of these valuable data. To solve these issues, we proposed a novel T2DM data repository framework, which was based on standards. This repository can integrate data from various sources. It would be used as a standardized record for further data transfer as well as integration. Phenotyping was conducted based on clinical guidelines with KNIME workflow. To evaluate the phenotyping performance of the proposed system, data was collected from local community by healthcare providers and was then tested using algorithms. The results indicated that the proposed system could detect DR cases with an average accuracy of about 82.8%. Furthermore, these results had the promising potential of addressing fragmented data. The proposed system has integrating and phenotyping abilities, which could be used for diabetes research in future studies.
Year
DOI
Venue
2018
10.1007/s10916-018-0939-0
J. Medical Systems
Keywords
Field
DocType
Archetype,Clinical data model,Clinical guideline,Diabetic retinopathy,Electronic health record,Phenotyping
Diabetic retinopathy,Data mining,Data collection,Disease,Database design,Information repository,Artificial intelligence,Chronic disease,Workflow,Medicine,Machine learning,Limiting
Journal
Volume
Issue
ISSN
42
7
0148-5598
Citations 
PageRank 
References 
2
0.38
11
Authors
10
Name
Order
Citations
PageRank
Huiqun Wu122.75
Yufang Wei220.72
Yujuan Shang321.06
Wei Shi420.38
Lei Wang531.15
jingjing li6418.67
Aimin Sang720.38
Lili Shi821.06
Kui Jiang99417.91
Jiancheng Dong1023.76