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Electronic medical record (EMR) system has become increasingly more important in developed countries due to its convenience and efficiency in medical information storage, management and analysis. However, one of the main limitations of EMR lies in that the clinical data for patients cannot be exchanged among different medical institutions. Recently, the cloud-based clinic system, featuring in lower...
It is a widely accepted fact that there is much tacit knowledge being used in daily medical practice, which remains to be unknown knowns, or inexpressible known knowns. On the other hand, health information systems developers are determined to make clinical information standardized, exchangeable, and machine-understandable to certain extent. This paper reports our experience in developing an applied...
Patient-specific records contained in Electronic Medical Record (EMR) systems are increasingly combined with genomic sequences and deposited into bio-repositories. This allows researchers to perform large-scale, low-cost biomedical studies, such as Genome-Wide Association Studies (GWAS) aimed at identifying associations between genetic factors and complex health-related phenomena, which are an integral...
First, the meaning of data mining from EMR with a view to discover valuable knowledge, as well as current problems is introduced. Then, several possible storage methods for EMR are deeply analyzed and studied. On this basis, the solution of storage XML EMR with DB2/9.5 hybrid database is presented. The XQ-Apriori algorithm based on classic Apriori algorithm and XML query language XQuery, as well as...
The aim of the present study is to design and develop a Decision Support System (DSS) closely coupled with an Electronic Medical Record (EMR), able to predict the risk of a Type 1 Diabetes Mellitus (T1DM) patient to develop retinopathy. The proposed system is able to store a wealth of information regarding the clinical state of the T1DM patient and continuously provide the health experts with predictions...
Comorbidity is quite common in the medical practice. In this article we explore a way to use anonymized Electronic Health Records (EHR) data in order to derive correlations, evidence based likelihood of comorbidities manifestation within the EHR patients population. The ultimate goal is to present the information to the health care provider at the moment when a new diagnosis is entered for the patient,...
Background: At present, passive alarm system from culture reports and announced from groups outbreak events make cases investigate delayed. Is there any predict factor can be used to suggest active high capture sensitivity surveillance and alarm outbreak early? Objectives: Is there any predict factor can be used to get active high capture sensitivity surveillance of hospital-acquired infections (HAI)...
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