Prados-Suárez B et al, Expert Systems with Applications, 2012
This paper aims to solve a recently arose problem, related to the access to the Electronic Health Records (EHR) in the Hospitals. Due to the digitalization of the information contained in the medical records, and the growing availability of devices that directly generate digital documents to include in it, the EHR are becoming unmanageable. Even more, to find a concrete item of information relevant for a given assistance act is a very hard, difficult and time-consuming task. To solve it we propose here the definition of contexts of access to the EHR, to exploit the logical division of the information inside each document in the EHR into data groups, and the computation of the pertinence of each data group to each context.
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Akinyokun CO et al, Medical and Care Compunetics 6, 2010
A neuro-fuzzy decision support system is proposed for the diagnosis of heart failure. The system comprises; knowledge base (database, neural networks and fuzzy logic) of both the quantitative and qualitative knowledge of the diagnosis of heart failure, neuro-fuzzy inference engine and decision support engine. The neural networks employ a multi-layers perception back propagation learning process while the fuzzy logic uses the root sum square inference procedure. The neuro-fuzzy inference engine uses a weighted average of the premise and consequent parameters with the fuzzy rules serving as the nodes and the fuzzy sets representing the weights of the nodes. The decision support engine carries out the cognitive and emotional filtering of the objective and subjective feelings of the medical practitioner.
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Marsh A et al, Medical and Care Compunetics 6, 2010
The European Union Future Internet Assembly, the roadmap for the Web heading towards semantic interoperability and building on the UK’s adoption of the Internet and social media are accelerating the development of Web 3.0. A number of health portals are opening, some with facilities for the capture of Patient Based Records. Collective Intelligence will be generated that, applied to health, has potential to support Public Health policy. By using the Internet, millions of people in the course of their daily activities contribute to uncertified data stores, some explicitly collaborating to create collective knowledge bases, some contributing implicitly through the patterns of their choices and actions.
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Pires, Gabriel, and Urbano Nunes, Journal of Intelligent and Robotic Systems, 34(3)
This paper describes new results with a Reactive Shared-Control system that enables a semi-autonomous navigation of a wheelchair in unknown and dynamic environments. The purpose of the reactive shared controller is to assist wheelchair users providing an easier and safer navigation. It is designed as a fuzzy-logic controller and follows a behaviour-based architecture.
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Akinyokun, Charles O. et al, IFMBE Proceedings 2009, 25/12
A neuro-fuzzy expert system is proposed for the diagnosis of heart failure. The system comprises; knowledge base (database, neural networks and fuzzy logic) of both the quantitative and qualitative knowledge of the diagnosis of heart failure, neuro-fuzzy inference engine and decision support engine. The decision support engine carries out the cognitive and emotional filtering of the objective and subjective feelings of the medical practitioner. An experimental study of the decision support system was carried out using cases of some from three hospitals in Nigeria with the assistance of their medical personnel who collected patients’ data over a period of six months. The results of the study show that the neuro-fuzzy system provides a highly reliable diagnosis, while the emotional and cognitive filters further refine the diagnosis results by taking care of the contextual elements of medical diagnosis.
Obot, Okure U., and Faith-Michael Uzoka, Medical and Care Compunetics 5, 2008
The application of the conventional symbolic rules found in knowledge base technology to the management of a disease suffers from its inability to evaluate the degree of severity of a symptom and by extension the degree of the illness. Fuzzy logic technology provides a simple way to arrive at a definite conclusion from vague, ambiguous, imprecise and noisy data (as found in medical data) using linguistic variables that are not necessary precise. In order to achieve this, a study of a knowledge base system for the management of diseases was undertaken. The Root Sum Square of drawing inference was employed to infer the data from the rules developed. This resulted in the establishment of some degrees of influence on the diseases. Using malaria as a case study, a system that uses Visual Basic .Net development environment was developed and the results of the computations are presented in this research.
Boissy, Patrick et al, Telemedicine and e-Health. December 2007, 13(6)
Fall detection and early medical response are challenging and promising aspects of home healthcare for older adults. A two-step algorithm for falls analyzed accelerometer data for 750 test events and found significance limits for body trunk angle change as well as falls. Automated detection of falls based upon motion sensing and fuzzy logic can be based upon evidence-derived rules.
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