Neural networks for estimation of hematocrit density from transduced current curve patterns

Proceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC

Volumn , Issue , 2008, Pages 1517-1520

  Huynh, Hieu Trung ^b   Won, Yonggwan ^a,b   Kim, Jung Ja ^c  

^a IEEE

^b Chonnam National University   (South Korea)

^c Chonbuk National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOSENSORS; BLOOD; DIELECTRIC DEVICES; ESTIMATION; FEEDFORWARD NEURAL NETWORKS; GLUCOSE; GLUCOSE OXIDASE; IMAGE CLASSIFICATION; VEGETATION;

ANALYSIS SYSTEM; ANODIC CURRENTS; CLINICAL DECISIONS; CURRENT CURVES; ELECTROCHEMICAL BIOSENSORS; FEED FORWARD; GLUCOSE MEASUREMENTS; GLUCOSE OXIDASES; HAND-HELD DEVICES; INFLUENCING FACTORS; INTERNATIONAL CONFERENCES; MEASURED VALUES; OUTPUT VALUES; WHOLE BLOOD;

NEURAL NETWORKS;

EID: 49249132551     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNSC.2008.4525461     Document Type: Conference Paper

References (12)

1. J. Z. Ma, J. Ebben, H. Xia, and A. J. Collins, "Hematocrit level and associated mortality in hemodialysis patients", J. Amer. Soc. Nephrol., vol. 10, 1999, pp. 610-619.
2. A. Aris, J. M. Padro, J. O. Bonnin, and J. M. Caralps, "Prediction of hematocrit changes in open-heart surgery without blood transfusion", J. Cardiovasc. Surg., vol. 25, no. 6, Nov-Dec. 1984, pp. 545-548.
3. R. F. Louie, Z. Tang, D. V. Sutton, J. H. Lee, G. J. Kost, "Point of Care Glucose Testing: effects of critical variables, influence of reference instruments, and a modular glucose meter design", Arch Pathol Lab Med, vol. 124, 2000, pp. 257-266.
4. Z. Tang, J. H. Lee, R. F. Louie, G. J. Kost, D. V. Sutton, "Effects of Different Hematocrit Levels on Glucose Measurements with HandHeld Meters for Point of Care Testing", Arch Pathol Lab Med, vol. 124, 2000, pp. 1135-1140.
5. E. S. Kilpatrick, A. G. Rumley, H. Myin, "The effect of variations in hematocrit, mean cell volume and red blood count on reagent strip tests for glucose", Ann Clin Biochem, vol. 30, 1993, pp. 485-487.
6. E. F. Treo, C. J. Felice, M. C. Tirado, M. E. Valentinuzzi, and D. O. Cervantes, "Hematocrit Measurement by Dielectric Spectroscopy", IEEE Transactions on Biomedical Engineering, vol. 25, no. 1, 2005, pp. 124-127.
7. P. J. G. Lisboa, E. C. Ifeachor, and P. S. Szczepaniak, "Artificial neural networks in Biomedicine", Springer-Verlag London Berlin Heidelberg, 2000.
8. R. N. G. Naguib, G. V. Sherbet,"Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management", CRC Press, Washington D.C., 2001.
9. G.-B. Huang, Q.-Y. Zhu, C.-K. Siew, "Extreme learning machine: Theory and applications", Neurocompuiing, vol. 70, 2006, pp. 489-501.
10. H. T. Huynh, J.-J. Kim and Y. Won, "An Improvement of Extreme Learning Machine for Compact Single-Hidden-Layer Feedforward Neural Networks", International Journal of Neural Systems, submitted, 2007.
11. G.-B. Huang, H. A. Babri, "Upper bounds on the number of hidden neurons in feedforward networks with arbitrary bounded nonlinear activation functions", IEEE Trans. on Neural Networks, vol. 9, no. 1, 1998, pp. 224-229.
12. P. L. Bartlett, "The Sample Complexity of Pattern Classification with Neural Networks: The Size of the Weights is More Important than the Size of the Network", IEEE Trans. on Inform. Theory, vol. 44, no. 2, 1998, pp. 525-536.