Niehaus, EHerselman, Martha EBabu, AN2010-01-282010-01-282009Niehaus, E, Herselman, M and Babu, AN. 2009. Principles of Neuroempiricism and generalization of network topology for health service delivery. Indian Journal of Medical Informatics, Vol. 4(1), pp 1-160973-0379http://ijmi.org/index.php/ijmi/article/view/y09i1a3/19http://hdl.handle.net/10204/3919Copyright: 2009 Indian Association of Medical InformaticsNeuroempiricism describes a strategy to store and process data analogous to the human brain and to derive an adaptive representation by modelling the biological processes. Technical systems often copy biological evolutionary “developments” from nature. The neuroempirical principle is an approach to realise features of biological information processing for technical approaches or solutions. It is a challenge to model spatial problems in healthcare like the dissemination of a viral infection. The characteristics of the infection are changing in time and often further complicated by unpredictable events such as mutation of the virus. These factors have to be accounted for in the computer based framework of the model. Artificial Neural Networks (ANN) can be used as a mathematical and informatics module embedded in a Decision Support System for risk assessment and the distribution of related medical services. This article describes the application of Neuroempiricism for modelling complex dynamic systems in healthcare informatics which results in a new extended network typology derived from a biological network. The new model extends directed weighted graphs to a topological non-equivalent network model that is able to represent biological axoaxonal junctions. The new network topology creates a data structure for computational decision support concepts. The Biological Neural Network (BNN) provides an extension of the ANN so that both fuzzy and crisp data can be processed in a unified network typology.enNeuroempiricismDecision support systemDSSNetwork topologyNeural networksArtificial neural networksBiological neural networkMedical informaticsHealth service deliveryArticleNiehaus, E., Herselman, M. E., & Babu, A. (2009). Principles of Neuroempiricism and generalization of network topology for health service delivery. http://hdl.handle.net/10204/3919Niehaus, E, Martha E Herselman, and AN Babu "Principles of Neuroempiricism and generalization of network topology for health service delivery." (2009) http://hdl.handle.net/10204/3919Niehaus E, Herselman ME, Babu A. Principles of Neuroempiricism and generalization of network topology for health service delivery. 2009; http://hdl.handle.net/10204/3919.TY - Article AU - Niehaus, E AU - Herselman, Martha E AU - Babu, AN AB - Neuroempiricism describes a strategy to store and process data analogous to the human brain and to derive an adaptive representation by modelling the biological processes. Technical systems often copy biological evolutionary “developments” from nature. The neuroempirical principle is an approach to realise features of biological information processing for technical approaches or solutions. It is a challenge to model spatial problems in healthcare like the dissemination of a viral infection. The characteristics of the infection are changing in time and often further complicated by unpredictable events such as mutation of the virus. These factors have to be accounted for in the computer based framework of the model. Artificial Neural Networks (ANN) can be used as a mathematical and informatics module embedded in a Decision Support System for risk assessment and the distribution of related medical services. This article describes the application of Neuroempiricism for modelling complex dynamic systems in healthcare informatics which results in a new extended network typology derived from a biological network. The new model extends directed weighted graphs to a topological non-equivalent network model that is able to represent biological axoaxonal junctions. The new network topology creates a data structure for computational decision support concepts. The Biological Neural Network (BNN) provides an extension of the ANN so that both fuzzy and crisp data can be processed in a unified network typology. DA - 2009 DB - ResearchSpace DP - CSIR KW - Neuroempiricism KW - Decision support system KW - DSS KW - Network topology KW - Neural networks KW - Artificial neural networks KW - Biological neural network KW - Medical informatics KW - Health service delivery LK - https://researchspace.csir.co.za PY - 2009 SM - 0973-0379 T1 - Principles of Neuroempiricism and generalization of network topology for health service delivery TI - Principles of Neuroempiricism and generalization of network topology for health service delivery UR - http://hdl.handle.net/10204/3919 ER -