Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805

This article is dedicated to the decision support, which has become one of the most promising and rapidly developing areas of application of modern intellectual and information technologies in various areas of professional activity, including problems in the automated medical diagnostics.

Modern level of artificial intelligence development allows us to develop programs that help to analyze all the data collected on the patient for their reasonable interpretation. The basic idea of medical decision support system is to build logic diagnosis setting process, correct from the medical point of view, and transparent for doctor.

For diagnosing automation, the state of bronchopulmonary system DSS DiaSpectrEx was developed. The analysis of changes in qualitative and quantitative composition of air exhaled by the patient is the source of information about the damage of the respiratory tract, inflammatory processes and the effectiveness of the treatment.

DiaSpectrEx system allows improving efficiency of pulmonary diseases diagnosing methods through the use of modern computerized equipment, machine learning algorithms and data processing. Development of high-precision medical decision support system enables non-invasive computerized pulmonary diagnostics.

DOI 10.15276/eltecs.23.99.2016.10

1. Guilan Kong, Dong-Ling Xu, and Jian-Bo Yang, (2008), Clinical Decision Support Systems: a Review on Knowledge Representation and Inference Under Uncertainties, International Journal of Computational Intelligence Systems (in English).

2. Josceli Maria Tenórioa, Anderson Diniz Hummela, et al., (2011), Artificial Intelligence Techniques Applied to the Development of a Decision Support System for Diagnosing Celiac Disease, International Journal of Medical Informatics (in English).

3. Komlevaya N., and  Cherneha K. Sredstva dlya kompleksnoy zaschityi informatsii v spetsializirovannoy diagnosticheskoy sisteme, [Tools for Comprehensive Protection of Information in a Specialized Diagnostic system], (2015), Tr. Shestnadtsatoy Mezhdunarodnoy Nauchno-prakticheskoy Konferentsii “Sovremennyie Informatsionnyie i Elektronnyie Tehnologii” - Odessa, Ukraine (In Russian).

4. Komlevaya N., and Komlevoy A. Avtomatizatsiya diagnostirovaniya sostoyaniya dyihatelnoy sistemy, [Automatization of Pulmonary System Diagnostics], (2012), Tr. Trinadtsatoy Mezhdunarodnoy Nauchno-prakticheskoy Konferentsii “Sovremennyie Informatsionnyie i Elektronnyie Tehnologii”, Odessa, Ukraine (In Russian).

5. Komlevaya N., Komlevoy A., and Tymchenko B. Sravnitelnyiy analiz dvuh podhodov pri reshenii zadachi klassifikatsii, [Comparative Analysis of Two Approaches to Solving the Problem of Classification], (2014), Nauko-tehnichniy Zhurnal “Radioelektronni i Komp’yuterni Sistemi”, Kharkov, Ukraine (In Russian).

6.Komlevoy A., Bazhora Yu., and Cherniavskyi V., (2014), The Differential Analysis of Seasonal Changes of the Moisture Condensate Macromolecular Structure of the Exhaled Air According to Laser Correlation Spectroscopy Data, British Journal of Science, Education and Culture. London University Press (In English).

7. Martin Riedmiller, (1994), Advanced Supervised Learning in Multilayer Perceptrons - From Backpropagation to Adaptive Learning Algorithms, Computer Standards and Interfaces (In English).

8. Sibi P., and Allwyn-Jones S., (2013),  Analysis of Different Activation Functions Using Back Propagation Neural Networks, Journal of Theoretical and Applied Information Technology (In English).

9. Kazemzadeh R.S., Sartipi K., and Jayaratna P., (2010), A Framework for data and Mined Knowledge Interoperability in Clinical Decision Support Systems, International Journal of Healthcare Information Systems and Informatics (In English).

10. Tymchenko B., (2015), Machine Learning Approach in Problems of Pulmonary Diagnostics, Materials IV Student Conference of Computer Science, Erfurt, Germany (In English)

11.Bazhora Yu.I., Komlevoy A.N., Chesnokova M.M., Nalazek A., and Zhukov W., (2013), Respiratory System Estimation at the Healthy Children and Children with Bronchitis with the Use of Laser Correlative Spectroscopy, Journal of Health Sciences, Vol. 3, No. 7(In English).

Last download:
29 May 2020

[ © KarelWintersky ] [ All articles ] [ All authors ]
[ © Odessa National Polytechnic University, 2014-2018. Any use of information from the site is possible only under the condition that the source link! ]