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The research on clinical data is one of the fastest growing fields all over the world. In general, most of the data have imbalanced issues, which may cause some problems in the researches. In this study, the methods of over-sampling and under-sampling are used for handling the issues of data imbalanced. The case based reasoning (CBR) is used for developing classification models to predict recurrent...
A description of patient conditions should consist of the changes in and combination of clinical measures. Traditional data-processing method and classification algorithms might cause clinical information to disappear and reduce prediction performance. To improve the accuracy of clinical-outcome prediction by using multiple measurements, a new multiple-time-series data-processing algorithm with period...
The clinical data stored in the health information system can be categorized as two types including structuralized data and non-structuralized ones. In the paper, a data extraction system is developed to assist data retrieval from the non-structuralized textual clinical documents such as radiology reports, pathology reports, etc. The system provides keyword-based and semantic-driven data matching...
This paper describes the method to create the HL7 message dynamically and make the HL7 middleware framework more efficient. The HL7 middleware framework was developed for exchanging the healthcare information in the National Taiwan University Hospital (NTUH). The framework is a Service-Oriented Architecture (SOA) and it contains the HL7Central Web Service. The Web Service makes the HL7 middleware...
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