Abstract
A fuzzy knowledge base encapsulating core expert rules for glaucoma follow up is developed and subsequently refined into a standard of care by reconciling several expert opinions. The Learning from Examples (LFE) [1] technique is used in addition to expert interviews to generate fuzzy rules from numerical data, and soft competition defines a fuzzy consensus metrics for the expert opinions. Web-based extension of this system into a comprehensive set of e-Health services for the glaucoma community enables, besides wide accessibility of the expert knowledge, continuous improvement of the core rule set (standard of care) with the perspectives of several experts.
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This work is funded under Collaborative Health Research Project Grant by the National Science and Engineering Research Council (NSERC) of Canada. We gratefully acknowledge the contributions of TransferTech GmbH Germany(www.Transfertech.de) with their soft computing software suite as well as their valuable insights in solving the implementation challenges we are faced with constantly.
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Ulieru, M., Crichton, A., Rizzi, M. et al. Using soft computing to define standards of care in glaucoma monitoring. Soft Computing 8, 705–716 (2004). https://doi.org/10.1007/s00500-003-0336-5
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DOI: https://doi.org/10.1007/s00500-003-0336-5