Determination of the composition of sialoliths composed of carbonate apatite and albumin using artificial neural networks

被引:4
|
作者
Kuzmanovski, I
Ristova, M
Soptrajanov, B
Stefov, V
Popovski, V
机构
[1] Univ Sv Kiril & Metodij, Inst Hemija, Skopje 1001, Macedonia
[2] Makedonska Akad Naukite & Umetnostite, Skopje 1000, Macedonia
[3] Univ Sv Kiril & Metodij, Klin Maksilofacijalna Hirurgija, Skopje 1001, Macedonia
关键词
salivary calculi; sialoliths; artificial neural networks; analysis; infrared spectroscopy; carbonate apatite; albumin;
D O I
10.1016/j.talanta.2003.10.009
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The determination of the components of the sialoliths is important both from the point of view of chances for a successful medical treatment of the patients and because the prevention of further re-occurrence of sialolithiasis depends upon the knowledge of the nature of the constituents of the concrements. Despite the fact that infrared spectroscopy is widely used for the determination of the composition of sialoliths, urinary calculi and bladder stones, we found no data for any chemometric method developed for such purposes. Here, a method is presented for quantitative determination of the content of salivary calculi composed of albumin and carbonate apatite (one of the most often found constituents in the analyzed calculi from the patients from Macedonia) using artificial neural networks (ANN). The results were checked on real samples using the standard addition method. The precision of the method was estimated using the relative standard deviation, which shows that it is suitable for routine analysis. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:813 / 817
页数:5
相关论文
共 50 条
  • [31] DETERMINATION OF POSITIONING ACCURACIES BY USING FINGERPRINT LOCALISATION AND ARTIFICIAL NEURAL NETWORKS
    Koyuncu, Hakan
    THERMAL SCIENCE, 2019, 23 : S99 - S111
  • [32] Honeycomb blocks composed of carbonate apatite, β-tricalcium phosphate, and hydroxyapatite for bone regeneration: effects of composition on biological responses
    Hayashi, K.
    Kishida, R.
    Tsuchiya, A.
    Ishikawa, K.
    MATERIALS TODAY BIO, 2019, 4
  • [33] Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
    Anysz, Hubert
    Narloch, Piotr
    MATERIALS, 2019, 12 (09)
  • [34] Algorithmic Music Composition Using Probabilistic Graphical Models and Artificial Neural Networks
    Marsden, Marc
    Ajoodha, Ritesh
    2021 SOUTHERN AFRICAN UNIVERSITIES POWER ENGINEERING CONFERENCE/ROBOTICS AND MECHATRONICS/PATTERN RECOGNITION ASSOCIATION OF SOUTH AFRICA (SAUPEC/ROBMECH/PRASA), 2021,
  • [35] Sawability prediction of carbonate rocks from shear strength parameters using artificial neural networks
    Kahraman, S
    Altun, H
    Tezekici, BS
    Fener, M
    INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, 2006, 43 (01) : 157 - 164
  • [36] Modeling the Mechanical Behavior of Carbonate Sands Using Artificial Neural Networks and Support Vector Machines
    Kohestani, V. R.
    Hassanlourad, M.
    INTERNATIONAL JOURNAL OF GEOMECHANICS, 2016, 16 (01)
  • [37] Critical clearing time determination of EGAT system using artificial neural networks
    Pothisarn, C
    Jiriwibhakorn, S
    2003 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-4, CONFERENCE PROCEEDINGS, 2003, : 731 - 735
  • [38] Catechol determination in compost bioremediation using a laccase sensor and artificial neural networks
    Tang, Lin
    Zeng, Guangming
    Liu, Jianxiao
    Xu, Xiangmin
    Zhang, Yi
    Shen, Guoli
    Li, Yuanping
    Liu, Can
    ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 2008, 391 (02) : 679 - 685
  • [39] Determination of on-road vehicle emission characteristics using artificial neural networks
    Eckhardt, U
    Palocz-Andresen, M
    Oetjen, PD
    Weber, T
    TM-TECHNISCHES MESSEN, 2005, 72 (09) : 524 - 530
  • [40] Flare performance modeling and set point determination using artificial neural networks
    Vijaya Durga Damodara
    Arokiaraj Alphones
    Daniel H. Chen
    Helen H. Lou
    Christopher Martin
    Xianchang Li
    International Journal of Energy and Environmental Engineering, 2020, 11 : 91 - 109