Application of Wavelet Neural Networks for Monitoring of Extraction of Carbon Multi-Functional Medical Nano-Agents from the Body

Abstract In the given study the new approach to solution of the problem of monitoring the removal of luminescent nanocomposites and their components from the body with urine is proposed. The monitoring is performed by luminescence spectra with the help of classical perceptron type neural networks and of wavelet neural networks. A comparative analysis of the results obtained with application of multilayer perceptrons and wavelet neural networks is carried out.

[1]  Alexander Efitorov,et al.  GPU-based high-performance computing of multichannel EEG phase wavelet synchronization , 2017, BICA.

[2]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[3]  O. Shenderova,et al.  Nanodiamond-Based Composite Structures for Biomedical Imaging and Drug Delivery. , 2015, Journal of nanoscience and nanotechnology.

[4]  I. G. Persiantsev,et al.  New opportunity solutions to inverse problems in laser spectroscopy involving artificial neural networks , 2002 .

[5]  J. Vávra,et al.  Coating nanodiamonds with biocompatible shells for applications in biology and medicine , 2017 .

[6]  Swathi Ramasahayam,et al.  Noninvasive Blood Glucose Sensing Using Near Infra-Red Spectroscopy and Artificial Neural Networks Based on Inverse Delayed Function Model of Neuron , 2014, Journal of Medical Systems.

[7]  Hua Jiang,et al.  Core-shell designs of photoluminescent nanodiamonds with porous silica coatings for bioimaging and drug delivery II: application. , 2013, Nanoscale.

[8]  V. L. Filardi,et al.  Classification of food vegetable oils by fluorimetry and artificial neural networks , 2015 .

[9]  Amir Amani,et al.  Cytotoxicity of chitosan/streptokinase nanoparticles as a function of size: An artificial neural networks study. , 2016, Nanomedicine : nanotechnology, biology, and medicine.

[10]  Jilong Wang,et al.  A review of carbon dots in biological applications , 2016, Journal of Materials Science.

[11]  Christopher Heil,et al.  Continuous and Discrete Wavelet Transforms , 1989, SIAM Rev..

[12]  O. Shenderova,et al.  Functionalization of graphene oxide nanostructures improves photoluminescence and facilitates their use as optical probes in preclinical imaging. , 2015, Nanoscale.

[13]  Winfried Denk,et al.  New developments in multiphoton microscopy , 2002, Current Opinion in Neurobiology.

[14]  O. Shenderova,et al.  A method for optical imaging and monitoring of the excretion of fluorescent nanocomposites from the body using artificial neural networks. , 2018, Nanomedicine : nanotechnology, biology, and medicine.

[15]  Ho Lee,et al.  Development of a high speed laser scanning confocal microscope with an acquisition rate up to 200 frames per second. , 2013, Optics express.

[16]  O. Shenderova,et al.  Monitoring of nanodiamonds in human urine using artificial neural networks , 2016 .

[17]  Young-In Kim.  Role of folate in colon cancer development and progression. , 2003, The Journal of nutrition.

[18]  J. Rao,et al.  Fluorescence imaging in vivo: recent advances. , 2007, Current opinion in biotechnology.

[19]  Andreas Reisch,et al.  Fluorescent Polymer Nanoparticles Based on Dyes: Seeking Brighter Tools for Bioimaging. , 2016, Small.

[20]  Markus Schwaiger,et al.  Imaging of integrin αvβ3 expression , 2008, Cancer and Metastasis Reviews.

[21]  S. Gambhir,et al.  Molecular imaging in living subjects: seeing fundamental biological processes in a new light. , 2003, Genes & development.

[22]  Sebastian Thrun,et al.  Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.

[23]  Giulia Bonacucina,et al.  Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks , 2014, International journal of nanomedicine.

[24]  K. A. Laptinskiy,et al.  Use of neural network algorithms for elaboration of fluorescent biosensors on the base of nanoparticles , 2013, Optical Memory and Neural Networks.

[25]  Qinghua Zhang,et al.  Wavelet networks , 1992, IEEE Trans. Neural Networks.

[26]  Jessica D. Schiffman,et al.  Quantum dots as fluorescent probes: Synthesis, surface chemistry, energy transfer mechanisms, and applications , 2018 .

[27]  A. Tonso,et al.  Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes , 2015, Bioprocess and Biosystems Engineering.

[28]  Yasar Becerikli,et al.  On three intelligent systems: dynamic neural, fuzzy, and wavelet networks for training trajectory , 2004, Neural Computing & Applications.

[29]  V. Mody,et al.  Novel nanomedicine-based MRI contrast agents for gynecological malignancies. , 2009, Advanced drug delivery reviews.