Prediction of chronic kidney disease using urinary dielectric properties and support vector machine

References

• Abdalla S, Al-Ameer S, Al-Magaishi S. 2010. Electrical properties with relaxation through human blood. Biomicrofluidics. 4(3):034101–034116.
   PubMed Web of Science ®Google Scholar
• Alison J, Sheppard R. 1993. Dielectric properties of human blood at microwave frequencies. Phys Med Biol. 38(7):971–978.
   Web of Science ®Google Scholar
• Alkhalaf A, Zürbig P, Bakker SJ, Bilo HJ, Cerna M, Fischer C, Fuchs S, Janssen B, Medek K, Mischak H. 2010. Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy. PLoS One. 5(10):e13421–e13431.
   PubMed Web of Science ®Google Scholar
• American Diabetes Association. 2014. Statistics about diabetes. National Diabetes Statistics Report. Retrieved from http://www.diabetes.org/diabetes-basics/statistics/
   Google Scholar
• Ban HJ, Heo JY, Oh KS, Park KJ. 2010. Identification of type 2 diabetes-associated combination of SNPS using support vector machine. BMC Genet. 11:26–36.
   Web of Science ®Google Scholar
• Barakat N, Bradley AP, Barakat MNH. 2010. Intelligible support vector machines for diagnosis of diabetes mellitus. IEEE Trans Inf Technol Biomed. 14(4):1114–1120.
   PubMedGoogle Scholar
• Bassey CE, Cowell S. 2013. Electrical properties of sucrose solutions for diabetic applications. Biophys J. 104(2):688a. doi: 10.1016/j.bpj.2012.11.3802
   Google Scholar
• Boresch S, Höchtl P, Steinhauser O. 2000. Studying the dielectric properties of a protein solution by computer simulation. J Phys Chem B. 104(36):8743–8752.
   Web of Science ®Google Scholar
• Feisul M, Azmi S. 2012. Management of chronic kidney disease in adults. National Diabetes Registry Report. Retrieved from http://www.msn.org.my/Doc/PublicDoc_PB/CPGManagementOfChronicKidneyDisease.pdf
   Google Scholar
• Ferry JD, Oncley J. 1938. Studies of the dielectric properties of protein solutions. Ii. The water-soluble proteins of normal horse serum1, 2. J Am Chem Soc. 60(5):1123–1132.
   Google Scholar
• Ganji MF, Abadeh MS. 2011. A fuzzy classification system based on ant colony optimization for diabetes disease diagnosis. Expert Syst Appl. 38(12):14650–14659.
   Web of Science ®Google Scholar
• Goldstein DE, Little RR, Lorenz RA, Malone JI, Nathan D, Peterson CM, Sacks DB. 2004. Tests of glycemia in diabetes. Diabetes Care. 27(7):1761–1773.
   PubMed Web of Science ®Google Scholar
• Gonzalez CA, Valencia JA, Mora A, Gonzalez F, Velasco B, Porras MA, Salgado J, Polo SM, Hevia-Montiel N, Cordero S. 2013. Volumetric electromagnetic phase-shift spectroscopy of brain edema and hematoma. PLoS One. 8(5):e63223–e63233.
   Web of Science ®Google Scholar
• Grant EH, Keefe SE, Takashima S. 1968. Dielectric behavior of aqueous solutions of bovine serum albumin from radiowave to microwave frequencies. J Phys Chem. 72(13):4373–4380.
   Web of Science ®Google Scholar
• Grewal PK, Golnaraghi F. 2014. Pilot study: Electrical impedance based tissue classification using support vector machine classifier. IET Sci Measurement Technol. 8(6):579–587.
   Web of Science ®Google Scholar
• Gronwald W, Klein MS, Zeltner R, Schulze BD, Reinhold SW, Deutschmann M, Immervoll AK, Böger CA, Banas B, Eckardt KU. 2011. Detection of autosomal dominant polycystic kidney disease by NMR spectroscopic fingerprinting of urine. Kidney Int. 79(11):1244–1253.
   PubMed Web of Science ®Google Scholar
• Haubitz M, Wittke S, Weissinger EM, Wellen M, Ruppech HD, Floege JU, Haller H, Michack H. 2005. Urine protein patterns can serve as diagnostic tools in patients with igA nephropathy. Kidney Int. 67(6):2313–2320.
   PubMed Web of Science ®Google Scholar
• Haykin S, Network N. 2004. Neural networks a comprehensive foundation. 2nd Ed. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Jaspard F, Nadi M, Rouane A. 2003. Dielectric properties of blood: An investigation of haematocrit dependence. Physiol Meas. 24(1):137–147.
   Web of Science ®Google Scholar
• Karabatak M, Ince MC. 2009. An expert system for detection of breast cancer based on association rules and neural network. Expert Syst Appl. 36(2):3465–3469.
   Web of Science ®Google Scholar
• Kerhet A, Raffetto M, Boni A, Massa A. 2006. A svm-based approach to microwave breast cancer detection. Eng Appl Artif Intell. 19(7):807–818.
   Web of Science ®Google Scholar
• Kistler AD, Mischak H, Poster D, Dakna M, Wüthrich RP, Serra AL. 2009. Identification of a unique urinary biomarker profile in patients with autosomal dominant polycystic kidney disease. Kidney Int. 76(1):89–96.
   PubMed Web of Science ®Google Scholar
• Laufer S, Rubinsky B. 2009. Tissue characterization with an electrical spectroscopy SVM classifier. IEEE Trans Biomed Eng. 56(2):525–528.
   Web of Science ®Google Scholar
• Liao X, Raghavan VGS, Meda V, Yaylayan VA. 2001. Dielectric properties of supersaturated d-glucose aqueous solution at 2450 MHZ. Journal of Microwave Power and Electromagnetics Energy. 36(3): 131–138.
   PubMed Web of Science ®Google Scholar
• Lonappan A, Bindu G, Thomas V, Jacob J, Rajasekaran C, Mathew KT. 2007. Diagnosis of diabetes mellitus using microwaves. J Electro Waves Appl. 21(10):1393–1401.
   Web of Science ®Google Scholar
• Lonappan A, Hamsakkutty V, Bindu G, Jacob J, Thomas V, Mathew K. 2004. Dielectric properties of human urine at microwave frequencies. Microwave Opt Technol Lett. 42(6):500–503.
   Web of Science ®Google Scholar
• Matyushov DV. 2012. On the theory of dielectric spectroscopy of protein solutions. J Phys: Condens Matter. 24(32):325105–325120.
   Web of Science ®Google Scholar
• Meriakri V, Chigrai E, Kim D, Nikitin I, Pangonis L, Parkhomenko M, Won J. 2007. Dielectric properties of glucose solutions in the millimetre-wave range and control of glucose content in blood. Meas Sci Technol. 18(4):1–6.
   Web of Science ®Google Scholar
• Michie D, Spiegelhalter DJ, Taylor CC (1994). Machine learning, neural and statistical classification. New York, NY: Overseas Press.
   Google Scholar
• Monnier L, Mas E, Ginet C, Michel F, Villon L, Cristol J-P, Colette C. 2006. Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes. J Am Med Assoc. 295(14):1681–1687.
   PubMed Web of Science ®Google Scholar
• Mun PS, Ting HN, Chong YB, Ong TA. 2015a. Dielectric properties of glycosuria at 0.2–50 GHZ using microwave spectroscopy. J Electrom Waves Appl. 1–15. doi: 10.1080/09205071.2015.1072480
   Google Scholar
• Mun PS, Ting HN, Ong TA, Wong CM, Ng KH, Chong YB. 2015b. A study of dielectric properties of proteinuria between 0.2 GHZ and 50 GHZ. PLoS One. 10(6):e0130011.
   Web of Science ®Google Scholar
• Nandi N, Bagchi B. 1998. Anomalous dielectric relaxation of aqueous protein solutions. J Phys Chem A. 102(43):8217–8221.
   Web of Science ®Google Scholar
• Oncley J. 1938. Studies of the dielectric properties of protein solutions. I. Carboxyhemoglobin1, 2. J Am Chem Soc. 60(5):1115–1123.
   Google Scholar
• Pethig R, Kell B. 1987. The passive electrical properties of biological systems: Their significance in physiology, biophysics and biotechnology. Phys Med Biol. 32(8):933–970.
   PubMed Web of Science ®Google Scholar
• Polat K, Güneş S, Arslan A. 2008. A cascade learning system for classification of diabetes disease: Generalized discriminant analysis and least square support vector machine. Expert Syst Appl. 34(1):482–487.
   Web of Science ®Google Scholar
• Rodríguez-Arteche I, Cerveny S, Alegría Á, Colmenero J. 2012. Dielectric spectroscopy in the ghz region on fully hydrated zwitterionic amino acids. Phys Chem Chem Phys. 14(32):11352–11362.
   Web of Science ®Google Scholar
• Roshan U, Chikkagoudar S, Wei Z, Wang K, Hakonarson H. 2011. Ranking causal variants and associated regions in genome-wide association studies by the support vector machine and random forest. Nucleic Acids Res. 39(9):e62–e62.
   Web of Science ®Google Scholar
• Shini MA, Laufer S, Rubinsky B. 2011. Svm for prostate cancer using electrical impedance measurements. Physiol Meas. 32(9):1373–1387.
   Web of Science ®Google Scholar
• Smulders PF, Buysse MG, Huang MD. 2013. Dielectric properties of glucose solutions in the 0.5–67 ghz range. Microwave Opt Technol Lett. 55(8):1916–1917.
   Web of Science ®Google Scholar
• Vapnik VN (1995). The nature of statistical learning theory. New York, NY: Springer-Verlag.
   Google Scholar
• Wentholt I, Kulik W, Michels R, Hoekstra JL, DeVries J. 2008. Glucose fluctuations and activation of oxidative stress in patients with type 1 diabetes. Diabetologia. 51(1):183–190.
   Web of Science ®Google Scholar
• Wolf M, Gulich R, Lunkenheimer R, Loid A. 2012. Relaxation dynamics of protein solution investigated by dielectric spectroscopy. Proteins Proteomics. 1–7.
   Web of Science ®Google Scholar
• Zürbig P, Decramer S, Dakna M, Jantos J, Good DM, Coon JJ, Bandin F, Mischak H, Bascands J-L, Schanstra JP. 2009. The human urinary proteome reveals high similarity between kidney aging and chronic kidney disease. Proteomics. 9(8):2108–2117. doi: 10.1002/pmic.200800560
   PubMed Web of Science ®Google Scholar