No abstract

The diagnosis is complex in domains where processes occur over time inside systems or objects, changing and affecting other processes and characteristics. A large number of knowledge-based systems have been developed to increase the efficiency of the diagnostic process. But the models of knowledge of such systems do not simultaneously take into account all types of temporal relationships: changes in the values of attributes over time, taking into account the time intervals that have passed from the moments when the process began to develop and external influences, and so forth. The article considers the universal ontology of knowledge about the diagnosis of processes in various domains as a generalization and the result of many years of experience of the authors in the creation of intelligent systems for the diagnosis of processes. The ontology allows us to formalize anomalies as developing internal processes that are not inherent in a normally functioning system. On its basis (in its terms) knowledge bases and software components for decision support systems are constructed. In the case of a need for a domain-oriented ontology, it will only be necessary to redefine some concepts and relations which are features of specific domains.

No abstract

The paper presents a cloud infrastructure for creation of interpretable diagnostic knowledge bases for intelligent decision support systems in medicine. An ontology of medical diagnostics allows us to form diseases regardless their etiology as a multivariate developing internal process. The relations types being defined in the ontology allow users to create a knowledge base sufficient for search of hypotheses of possible single diagnoses, for detection of combined and complicated pathologies, and for reduction of a set of hypotheses of diagnosis. The offered infrastructure includes the following tools: the knowledge base editor being generated on ontology, the terminology database editor, the tool for estimation of knowledge base quality and some instruments of automation of development and improvement of knowledge base. The infrastructure is implemented on the IACPaaS platform and used by experts to create knowledge bases in various fields of medicine. The article is useful for developers of medical diagnostics systems.