Ontological Framework for Constructing Hybrid Prognoses and Risk Assessment of Critical Conditions of Patients

The paper describes a cloud-based ontological framework for designing hybrid cloud software systems and services for predicting patient conditions and assessing the risk of critical conditions and events. The proposed solution is based on integrated semantic models for the formation of knowledge, documents, hypotheses and reasoned decisions in medicine. These complexes combine several types of sources for the formation of knowledge bases and various methods and approaches to solving such problems (mathematical modeling, machine learning, and knowledge engineering). For a group of diseases or a section of medicine, knowledge bases are formed about diseases that have passed the verification procedure or that doctors are ready to trust a priori. The means of declarative description of the rules of interpretation of knowledge about the dynamics of the development of diseases and numerical values from predictive models are provided.