On the Nonbinary Version of the Causality Relation in the Intelligent Analysis of Oncological Data

Abstract

The experience and specifics of the use of intelligent data analysis (IDA) in high-tech medical diagnostics are discussed. The current version of the IDA is a mathematical formalization of the so-called causal similarity heuristic by algebraic means. The main features and abilities of the developed approach are demonstrated in relation to the tasks of the diagnosis and treatment of certain types of human brain tumors. Some results characterizing the causality of the effect of pseudo-progression and tumor recurrence are presented. The potential and prospects of the developed approaches and diagnostic tools in the arsenal of modern evidence-based medicine are considered.