Mazepa E.A., Grishina O.V., Levshinsky V.V., Suleymanova Kh.M. The Unification of Microvawe Radio Thermometry Method

https://doi.org/10.15688/mpcm.jvolsu.2017.6.4

Elena Alekseevna  Mazepa
Candidate of Physical and Mathematical Sciences, Senior Researcher,
Department of Mathematical Analysis and Function Theory,
Volgograd State University
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Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Olga Viktorovna Grishina
Master Student, Department of Computer Science and Experimental Mathematics,
Volgograd State University
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Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Vladislav Viktorovich  Levshinsky
Master Student, Department of Mathematical Analysis and Function Theory,
Volgograd State University
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Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Khedi Movladovna Suleymanova
Postgraduate Student, Department of Mathematical Analysis and Function Theory,
Volgograd State University
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Prosp. Universitetsky, 100, 400062 Volgograd, Russian Federation

Abstract.  Mathematical  description  of  the  diagnostic  features,  finding  their quantitative  characteristics,  as  well  as  identifying  new  diagnostic  features  are  very important stages in creating an effective intelligent advisory system. The paper presents a unification method of analyzing information and finding a universal algorithm for searching highly  informative  diagnostic  features  from  the  data  of  microwave  radiometry.  The classification  of  thermometric  diagnostic  features  indicating  different  anomalies  of temperature fields have been classified.

Modern methods and possibilities of treating many types of diseases are such that achieving a positive result is possible only if they are detected at the earliest possible stage of development. In addition, it is known that many pathological processes change the  normal  temperature  distribution  both  on  the  surface  of  the  body  and  inside  it.

Moreover, many structural changes in tissue are preceded by an abnormal temperature change. This fact is the basis of the diagnostic method – microwave radio thermometry (RTM-method), which is of exceptional interest for the early diagnosis of cancer and a number of other pathologies.

The proposed approach allows to obtain new medical knowledge regarding the behavior of the temperature fields of patients. Namely, the study of differential analogues of second derivatives  of  temperature’s  functions  has  discovered  a  whole  group  of  qualitatively  new diagnostic signs. The application may well improve the results of classification of the expert system. However, the justification of the results will be based on high information characteristics. The authors also note that the real sensitivity and specificity of the advisory system should be identified through trial operation, i.e. more interesting is the question of how much they improve the diagnostics performed by specialists.

Key words: data mining, microwave radio thermometry, intelligent advisory systems, highly informative features.

Creative Commons License

The Unification of Microvawe Radio Thermometry Method by Mazepa E.A., Grishina O.V., Levshinsky V.V., Suleymanova Kh.M. is licensed under a Creative Commons Attribution 4.0 International License.

Citation in English: Mathematical Physics and Computer Simulation. Vol. 20 No. 6 2017 pp. 38-50

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