A.G. Losev1, I.E. Popov2, A.G. Gudkov3, S.V. Chizhikov4

1,2 Volgograd State University (Volgograd, Russia)
3 4 Bauman Moscow State Technical University (Moscow, Russia)
3 LLC Research and Production Innovation Firm HYPERION (Moscow, Russia)
 

This paper describes and substantiates the prospects for the use of artificial intelligence in medical diagnostics based on the method of microwave radiothermometry. In particular, an original method for the development of hybrid intelligent decision support systems in the diagnosis of breast cancer based on mathematical modeling and intellectual analysis of thermometric data is proposed.

This method of medical diagnostics is based on the measurement of the intrinsic electromagnetic radiation of human tissues in the microwave and infrared ranges, which makes it possible to non-invasively detect temperature anomalies at a depth of several centimeters. It is assumed that such a system should include a classification model and a classifier interpretation model, according to which the justification of the results is built in a language understandable to a specialist. A method for developing diagnostic and conceptual-diagnostic models is proposed, which consists in the phased creation and subsequent refinement of the corresponding models. The process begins with the creation of a conceptual model that describes the temperature anomalies characteristic of each of the diagnostic classes. Then a mathematical model is built that quantitatively describes each of the anomalies. A diagnostic model is built on the basis of the mathematical model. This model is based on a classification algorithm, the input of which is a feature space, which includes elements of a mathematical model. The final one is the conceptual-diagnostic model, which, on the basis of the diagnostic model, builds a rationale for the supplied diagnostic solution. The paper provides examples of each of these models used in breast cancer examinations using microwave radiothermometry. It also describes the diagnostic classes used in examinations, as well as the temperature anomalies characteristic of each of them. A mathematical model is presented and the principles of its construction are described. The results of computational experiments on the constructed diagnostic models are described, showing their effectiveness. Examples of consultative-diagnostic models based on various classification algorithms are given. The proposed methods for constructing intelligent systems can be applied both in conducting examinations of other organs using microwave radiothermometry, and adapted to various other areas of application that use classification algorithms that are subject to justification.

The method of microwave radiothermometry has been used in medical centers in Russia and the world over the past 25 years and has already shown quite good efficiency. The paper shows that one of the main prospects for the development of this diagnostic method is the use of artificial intelligence algorithms and the development of appropriate intelligent systems.

The research was carried out with the financial support of the Russian science Foundation in the framework of agreement No. 19-19-00349-П in the theme: «A method and a multichannel multifrequency microwave radiothermography on the basis of monolithic integrated circuits for finding the 3D distribution and dynamics of brightness temperature in the depths of the human body».

Losev A.G., Popov I.E., Gudkov A.G., Chizhikov S.V. Intelligent analysis of microwave radiothermometry data in medical diagnostics. Nanotechnology: development and applications – XXI century. 2023. V. 15. № 1. P. 5–22. DOI: https://doi.org/10.18127/ j22250980-202301-01 (in Russian)

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