Strategy maintenance in smart healthcare systems

Abstract

Backgrounds The size of medical strategies is expected to grow in conjunction with the expansion of modern diseases’ complexity. When a strategy includes more than ten statements, its manual management becomes very challenging, and in some cases, impossible. As a result, the updates they get may result in the unavoidable appearance of anomalies. This causes an interruption in the outflow of imperfect knowledge. Methods In this paper, we propose an approach called TAnom-HS to verify healthcare strategies. We focus on the management and maintenance, in a convenient and automatic way, of a large strategy to guarantee knowledge accuracy and enhance the efficiency of the inference process in healthcare systems. Results We developed a prototype of our proposal and we applied it on some cases from the BioPortal repository. The evaluation of both steps of TAnom-HS proved the efficiency of our proposal. Conclusion To increase ontologies expressiveness, a set of rules called strategy is added to it. TAnom-HS is a two-step approach that treats anomalies in healthcare strategies. Such a task helps to take automatic and efficient healthcare decisions.