- At the Interface between Medical Informatics and Personalized Medicine: The eMERGE Network Experience
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Chisholm R
- KMID: 2229486
- Healthc Inform Res.
- 2013 Jun;19(2):67-68.
- doi: 10.4258/hir.2013.19.2.67
No abstract available. -
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- Book Review: Spatial Analysis in Epidemiology
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Choi M
- KMID: 2229496
- Healthc Inform Res.
- 2013 Jun;19(2):148-149.
- doi: 10.4258/hir.2013.19.2.148
No abstract available. -
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- Potentiality of Big Data in the Medical Sector: Focus on How to Reshape the Healthcare System
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Jee K, Kim GH
- KMID: 2229488
- Healthc Inform Res.
- 2013 Jun;19(2):79-85.
- doi: 10.4258/hir.2013.19.2.79
OBJECTIVES: The main purpose of this study was to explore whether the use of big data can effectively reduce healthcare concerns, such as the selection of appropriate treatment paths, improvement... -
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- Nursing Informatics: Decades of Contribution to Health Informatics
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Moen A, Maeland Knudsen LM
- KMID: 2229489
- Healthc Inform Res.
- 2013 Jun;19(2):86-92.
- doi: 10.4258/hir.2013.19.2.86
OBJECTIVES: In this paper we present a contemporary understanding of "nursing informatics" and relate it to applications in three specific contexts, hospitals, community health, and home dwelling, to illustrate achievements... -
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- Information System Success Model for Customer Relationship Management System in Health Promotion Centers
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Choi W, Rho MJ, Park J, Kim KJ, Kwon YD, Choi IY
- KMID: 2229492
- Healthc Inform Res.
- 2013 Jun;19(2):110-120.
- doi: 10.4258/hir.2013.19.2.110
OBJECTIVES: Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This... -
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- Trends in Health Information Technology Safety: From Technology-Induced Errors to Current Approaches for Ensuring Technology Safety
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Borycki E
- KMID: 2229487
- Healthc Inform Res.
- 2013 Jun;19(2):69-78.
- doi: 10.4258/hir.2013.19.2.69
OBJECTIVES: Health information technology (HIT) research findings suggested that new healthcare technologies could reduce some types of medical errors while at the same time introducing classes of medical errors (i.e.,... -
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- Role of Computerized Physician Order Entry Usability in the Reduction of Prescribing Errors
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Peikari HR, Zakaria MS, Yasin NM, Shah MH, Elhissi A
- KMID: 2229490
- Healthc Inform Res.
- 2013 Jun;19(2):93-101.
- doi: 10.4258/hir.2013.19.2.93
OBJECTIVES: Some hospitals have implemented computerized physician order entry (CPOE) systems to reduce the medical error rates. However, research in this area has been very limited, especially regarding the impact... -
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- Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital
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Shin SY, Lyu Y, Shin Y, Choi HJ, Park J, Kim WS, Lee JH
- KMID: 2229491
- Healthc Inform Res.
- 2013 Jun;19(2):102-109.
- doi: 10.4258/hir.2013.19.2.102
OBJECTIVES: The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect... -
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- Computational Approach for Protein Structure Prediction
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Venkatesan A, Gopal J, Candavelou M, Gollapalli S, Karthikeyan K
- KMID: 2229495
- Healthc Inform Res.
- 2013 Jun;19(2):137-147.
- doi: 10.4258/hir.2013.19.2.137
OBJECTIVES: To predict the structure of protein, which dictates the function it performs, a newly designed algorithm is developed which blends the concept of self-organization and the genetic algorithm. METHODS: Among... -
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- Modified Mixture of Experts for the Diagnosis of Perfusion Magnetic Resonance Imaging Measures in Locally Rectal Cancer Patients
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Myoung S
- KMID: 2229494
- Healthc Inform Res.
- 2013 Jun;19(2):130-136.
- doi: 10.4258/hir.2013.19.2.130
OBJECTIVES: This study demonstrates the feasibility of using a modified mixture of experts (ME) model with repeated measured tumoural Ktrans value to perform an automatic diagnosis of responder based on perfusion... -
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- Use of Data Mining Techniques to Determine and Predict Length of Stay of Cardiac Patients
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Hachesu PR, Ahmadi M, Alizadeh S, Sadoughi F
- KMID: 2229493
- Healthc Inform Res.
- 2013 Jun;19(2):121-129.
- doi: 10.4258/hir.2013.19.2.121
OBJECTIVES: Predicting the length of stay (LOS) of patients in a hospital is important in providing them with better services and higher satisfaction, as well as helping the hospital management... -
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