The IACPaaS platform provides ample opportunities for developing systems based on knowledge in medicine. One example of such a system is the "Software system for creating medical intelligent systems."

In the modern world, various classes of medical intellectual systems (IS) exist and are constantly being developed, such as: expert systems for diagnosis of diseases (one or group) and treatment purposes, virtual medical simulators-simulators for working out, first of all, motor-reflex skills of students. However, such systems are disjointed, databases and knowledge are usually not available to domain experts for viewing and modification, which significantly reduces the credibility of them and makes it impossible to make timely changes (adding knowledge in connection with changing the domain, correcting errors and inaccuracies).

The software system for creating medical intelligent systems for practical and educational medicine is an integrated environment that supports the creation of the following types of intelligent systems: diagnosis and differential diagnosis of diseases, treatment design, its prognosis and monitoring, as well as computer simulators for diagnosis and appointment treatment.

The knowledge base management system is based on a problem-oriented model of knowledge representation and data, taking into account the specificity of the given subject area (medicine). It contains a set of ontologies for building knowledge bases and databases. Each ontology is a system of concepts understood by experts in the field of medicine, in terms of which they can form knowledge bases and databases without intermediaries in the person of knowledge engineers and system analysts. Ontologies have a graph representation with loops and loops.

The peculiarity of the system is a common set of ontologies and, accordingly, knowledge and data bases formed on them, which will be used again in medical intelligent systems of various types. All ontologies do not depend on the division of medicine.


We are developing a software shell for the systems of verification of intuitive mathematical proofs, which allows us to create application support systems for building (verification) evidence, based on core formal system, close to the mathematical practice of constructing intuitive mathematical proofs, and provides the tools of extension of this system.

To enable the formal logic system to approach the mathematical practice, it must be expandable, primarily by users of the DSSs based on it - members of the mathematical community.

The following components of the formal system are extensible and mutable: the language of representation of mathematical knowledge, which describes axioms, theorems, lemmas, definitions, etc., and a set of formalized ways of reasoning, available mathematics in the construction of the proofs of theorems. To do this, the reasoning methods are presented explicitly, and the presentation language formalized reasoning is also extensible.

To ensure the extensibility of formal systems, they use an approach based on context-dependent grammars and ontologies. Extensibility is achieved due to the fact that the context-dependent grammars of the abstract and concrete syntax of the representation languages ​​of mathematical knowledge and formalized methods of reasoning have in the DSS an explicit declarative representation specified in accordance with the metamodel (consisting of the description language of generating graph grammars, context description language, and description language of generative text grammars). Due to this, firstly, the methods of reasoning (calculus) have an explicit declarative representation in the DSS, and therefore, users can change their set, as well as the ways of reasoning; Secondly, users have the opportunity to include in the grammar of the language representation of mathematical knowledge new rules or modify existing ones. The same applies to contextual conditions.