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Medical fuzzy-expert system for prediction of engraftment degree of dental implants in patients with chronic liver disease

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Identyfikatory
Warianty tytułu
PL
Medyczny rozmyty system ekspercki do przewidywania stopnia wszczepienia implantów dentystycznych u pacjentów z przewlekłąchorobą wątroby
Języki publikacji
EN
Abstrakty
EN
The paper presents an information technology for assessing the degree of engraftment of dental implants in the event of a pathology violation through the use of fuzzy sets, which allows using this method for medical diagnostic tasks. Main scientific results: developed algorithms and mathematical models that formalize the process supporting diagnostic decisions based on fuzzy logic; developed mathematical models of membership functions that formalize the presentation of qualitative and qualitative informational features based on the rules of fuzzy logic, which can be used in information expert systems when assessing the degree of engraftment of dental implants in case of disease with pathological diseases.
PL
W artykule przedstawiono technologię informacyjną do oceny stopnia wszczepienia implantów stomatologicznych u pacjentów z przewlekłą chorobą wątroby za pomocą zbiorów rozmytych, co pozwala na zastosowanie tej metody do medycznych zadań diagnostycznych. Główne wyniki naukowe: opracowano algorytmy i modele matematyczne formalizujące proces wspomagania podejmowania decyzji diagnostycznych w oparciu o logikę rozmytą; opracowano matematyczne modele funkcji przynależności formalizujące reprezentację ilościowych i jakościowych cech informacyjnych opartych na regułach logiki rozmytej, które mogą być wykorzystane w informatycznych systemach ekspertowych do oceny stopnia wszczepienia implantów stomatologicznych u pacjentów z przewlekłą chorobą wątroby.
Rocznik
Strony
90--94
Opis fizyczny
Bibliogr. 31 poz., tab., rys.
Twórcy
  • National Pirogov Memorial Medical University, Vinnytsia, Ukraine
  • Vinnytsia National Technical University, Vinnytsia, Ukraine
  • National Pirogov Memorial Medical University, Vinnytsia, Ukraine
  • National Pirogov Memorial Medical University, Vinnytsia, Ukraine
  • National Pirogov Memorial Medical University, Vinnytsia, Ukraine
  • Vinnytsia National Technical University, Vinnytsia, Ukraine
  • Institute of Information and Computing Technologies of the CS MES RK. Almaty, Kazkhstan
  • Al-Farabi Kazakh National University, Almaty, Kazkhstan
Bibliografia
  • [1] Abdelhay N., Prasad S., Gibson M. P.: Guided versus non-guided dental implant placement: a systematic review and meta-analysis. BDJ Open. 7(1), 2021, 31.
  • [2] Arunyanak S. P. et al.: The effect of factors related to periodontal status toward peri-implantitis. Clin Oral Implants Res. 30(8), 2019, 791–799.
  • [3] Atieh M. A. et al.: Interventions for replacing missing teeth: alveolar ridge preservation techniques for dental implant site development. Cochrane Database of Systematic Reviews 4, 2021, CD010176.
  • [4] Bertolini M. M. et al.: Does traumatic occlusal forces lead to peri-implant bone loss? A systematic review. Braz Oral Res. 33(suppl 1), 2019, e069.
  • [5] Clinical guidelines for the management of pulpal diseases, approved by Decree 15 of the Council of Public Association: Russian Dental Association. 2018.
  • [6] Demkovich A. E., Yakymchuk M. M., Sverstyuk A. S.: Etiological risk factors for the occurrence of peri-implantitis. Clinical dentistry 2(31), 2020, 62–69.
  • [7] Guo Y. et al.: Influence of marginal bone resorption on two mini implant retained mandibular overdenture: An in vitro study. J Adv Prosthodont. 13(1), 2021, 55–64.
  • [8] Katelyan O. V. et al.: Study of the peripheral blood circulation of an abdominal wall using optoelectronic plethysmograph. W.Wojcik et al. (eds): Information Technology in Medical Diagnostics II. CRC Press, Balkema book, Taylor & Francis Group, London, UK, 2019, 119–125.
  • [9] Kozlovska T. I. et al.: Device to determine the level of peripheral blood circulation and saturation. Proc. SPIE 10031, 2016, 100312Z.
  • [10] Nizhynska-Astapenko Z. et al.: Information medical fuzzy-expert systemfor the assessment of the diabetic ketoacidosis severity on the base of the blood gases indices. Proc. SPIE 12126, 2021.
  • [11] Pavlov S. V. et al.: Analysis of microcirculatory disorders in inflammatory processes in the maxillofacial region on based of optoelectronic methods. Przeglad Elektrotechniczny 93(5), 2017, 114–117.
  • [12] Pavlov S. V. et al.: Electro-optical system for the automated selection of dental implants according to their colour matching. Przeglad Elektrotechniczny 93(3), 2017, 121–124.
  • [13] Pelekhan B. L., Rozhko M. M.: Bone tissue resorption around intraosseous dental implants in patients with mandible edentulousness. Stomatological Bulletin 121(4), 2023, 55–62.
  • [14] Pelekhan B. et al.: Analytical Modeling of the Interaction of a Four Implant Supported Overdenture with Bone Tissue. Materials 15(7), 2022, 2398.
  • [15] Polishchuk S. S., Skyba V. Ya., Davydenko I. S.: Histological changes of bone tissue in the perforation defect site of the rat mandibule when using hepatoprotector in odstructive hepatitis. World of medicine and biology 16(72), 2020, 193–198.
  • [16] Polishchuk V. S., Polishchuk S. S.: Peculiarities of the course after the operative course of patients after dental implantation on the background of the pathology of the hepatobilier system. Stomatological Bulletin 120(3), 2022, 51–56.
  • [17] Rotshtein A.: Design and Tuning of Fussy IF –THEN Vuly for Medical Didicol Diagnosis. H.-N.L Teodorescu, et al. (eds): Fuzzy and Neuro-Fuzzy Systems in Medicine. CRC-Press, 1998, 235–295.
  • [18] Sidor O. V.: The strategy for planning surgical stage dental implantation. Stomatological Bulletin 118(1), 2022, 50–55.
  • [19] Semenov Ye. I. et al.: Comparative characteristics of dental defects and the volume of implantological care in the young population of Ukraine. Stomatological Bulletin 119(2), 2022, 60–65.
  • [20] Serkova V. K. et al.: Medical expert system for assessment of coronary heart disease destabilization based on the analysis of the level of soluble vascular adhesion molecules. Proc. SPIE 10445, 2017, 104453O.
  • [21] Shkilniak L. et al.: Expert fuzzy systems for evaluation of intensity of reactive edema of soft tissues in patients with diabetes. Informtyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska – IAPGOS, 2022, 3, 59–63.
  • [22] Taubayev G. et al.: Machine learning algorithms and classificationof textures. Journal of Theoretical and Applied Information Technologythis 98(23), 2020, 3854–3866.
  • [23] Ushenko Yu. A., Sidor M. I., Bodnar G. B.: Mueller-matrix mapping of optically anisotropic fluorophores of biological tissues in the diagnosis of cancer. Quanrum Electron. 44(8), 2014, 785–790.
  • [24] Ushenko V. A., Gavrylyak M. S.: Azimuthally invariant Mueller-matrix mapping of biological tissue in differential diagnosis of mechanisms protein molecules networks anisotropy. Proc. SPIE 8812, 2016, 88120Y.
  • [25] Vasilevskyi O. et al.: Method of evaluating thelevel of confidence basedon metrological risks for determining the coverage factorin the concept of uncertainty. Proc. SPIE. 10808, 2018, 108082C.
  • [26] Vassilenko V. et al.: Automated features analysis of patients with spinal diseases using medical thermal images. Proc. SPIE 11456, 2020, 114560L.
  • [27] Wójcik W. et al. (eds): Information Technology in Medical Diagnostics. CRC Press, 2017.
  • [28] Wójcik W. et al. (eds): Information Technology in Medical Diagnostics II. Taylor & Francis Group. CRC Press, Balkema Book, London, 2019.
  • [29] Wójcik W. et al.: Medical Fuzzy-Expert System for Assessment of the Degree of Anatomical Lesion of Coronary Arteries. Int. J. Environ. Res. Public Health 20(2), 2023, 979 [https://doi.org/10.3390/ijerph20020979].
  • [30] Zabolotna N. I. et al.: Diagnostics of pathologically changed birefringent networks by means of phase Mueller matrix tomography. Proc. SPIE 8698, 2013, 86980C.
  • [31] Zabolotna N. I. et al.: System of polarization phasometry of polycrystalline blood plasma networks in mammary gland pathology diagnostics. Proc. SPIE 9613, 2015, 961311.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ceb71a94-5f58-4ba2-9e60-7bb05d415739
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