Cloud Environment for Development and Use of Software Systems for Clinical Medicine and Education

Abstract

A review of modern software systems which solve different medical problems shows that there is a need for unified software-information environment which could provide access: for physicians to intelligent systems of decision support; for experts to knowledge bases and databases for their refinement and keeping in actual state; for students to simulators and training courses in different fields of medicine. Thus a concept of a cloud environment for development and use of a medical intelligent systems community is proposed. This environment concentrates medical information and software resources in a single virtual space and provides users with a wide access regardless of their geographical position. Information resources are ontologies (they define the structure of terms), knowledge bases and databases. Software resources are problem solvers (applied ones and system tools). Applied solvers are expert systems for decision support, case record editors, simulators, etc. System tools provide creation and management for information and software resources. Keywords-medical intelligent systems, cloud environment, ontology, knowledge base, observations base, disease, expert systemI.

An Intelligent System for Medical Decision Support in Differential Diagnosis and Treatment of COVID-19

“…Components of the differential diagnosis of COVID-19. To solve diagnostic problems on the medical portal of the IACPaaS cloud platform [ 21 ], the already mentioned “Knowledge Ontology of Disease Diagnostics,” “Knowledge Base of Viral Diseases,” as well as software components that provide data processing were placed as information resources: “Intelligent Problem Solver of Diagnostic Problems and Differential Diagnostics” and “Service for Entering an Electronic Medical Record.”…”

Knowledge-Based Systems Manufacturing With Viability Ensuring

“…We compared the process of building a complex of interconnected developing knowledge bases to build a medical decision support system for the diagnosis and treatment of diseases using the Protege (Musen 2015) and IACPaaS tools (Gribova et al 2019). For this purpose, we have created classi ers of diseases, symptoms and medicines on the Protege platform.…”