Studies in health technology and informatics
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Stud Health Technol Inform · Jan 2014
Computer assisted treatment prediction of low back pain pathologies.
The paper presents a fuzzy inference system based prediction with the role to determine the appropriate action for patients that presents lower back pain. If not treated correctly lower back pain can degenerate in various diseases. ⋯ In total 243 rules have been formulated but only 21% of the rules suggests surgery. The initial results are promising; there is a correlation of 0.83% between the control results and the results from the system.
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Patient-Centric Care requires comprehensive visibility into the strengths and vulnerabilities of individuals and populations. The systems involved in Patient-Centric Care are numerous and heterogeneous, span medical, behavioral and social domains and must be coordinated across government and NGO stakeholders in Health Care, Social Care and more. We present a system, based on Linked Data technologies, taking first steps in making this cross-domain information accessible and fit-for-use, using minimal structure and open vocabularies. We evaluate our system through user studies.
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Stud Health Technol Inform · Jan 2014
The design and implementation of a ubiquitous personal health record system for South Africa.
Doctors can experience difficulty in accessing medical information of new patients. One reason for this is that, the management of medical records is mostly institution-centred. The lack of access to medical information may affect patients in several ways, such as: new medical tests may be carried out at a cost to the patient, and doctors may prescribe drugs to which the patient is allergic. ⋯ The design was informed by a literature review of existing personal health record standards, applications and the need to ensure patient privacy. Three medical practices in Port Elizabeth were interviewed with the aim of contextualizing the personal health record standards from the literature study. The findings of this research provide an insight as to how patients can bridge the gap created by institution-centred management of medical records.
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Stud Health Technol Inform · Jan 2014
Prediction of the prognosis of ischemic stroke patients after intravenous thrombolysis using artificial neural networks.
In general, around 80% of all strokes are ischemic. Take caring of the patients who have suffered an ischemic stroke is both expensive and time consuming. It is known that thrombolysis in patients with ischemic stroke can reduce the disability and increase the survival rate, however some patients still have poor outcomes. ⋯ The sensitivity, specificity and accuracy for model 1 were 77.78%, 80.43% and 79.27%, respectively, and 94.44%, 95.65% and 95.12%, respectively, for model 2. Artificial neural networks are used to establish prediction models with good performance to predict thrombolysis outcomes. These models may be able to help physicians to discuss and explain the likely outcomes to patients and their families before thrombolysis treatment.
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Stud Health Technol Inform · Jan 2014
Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL.
Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. ⋯ The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.