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A Novel Method for Diagnosing Cirrhosis in Patients with Chronic Hepatitis B: Artificial Neural Network Approach

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Abstract

We designed an artificial neural network (ANN) to diagnose cirrhosis in patients with chronic HBV infection. Routine laboratory data (PT, INR, platelet count, direct bilirubin, AST/ALT, AST/PLT) and age were collected from 144 patients. Cirrhosis in these patients was diagnosed by liver biopsy. The ANN’s ability was assessed using receiver-operating characteristic (ROC) analysis and the results were compared with a logistic regression model. Our results indicate that the neural network analysis is likely to provide a non-invasive, accurate test for diagnosing cirrhosis in chronic HBV-infected patients, only based on routine laboratory data.

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References

  1. Dennis, L. K., Eugene, B., Anthony, F., Stephen, H., Dan, L., and Larry, J., Harrison’, s principles of internal medicine, 16th edition. Mc Graw Hill, New York, 2005.

    Google Scholar 

  2. Heidelbaugh, J. J., and Bruderly, M., Cirrhosis and chronic liver failure: part I. Diagnosis and evaluation. Am. Fam. Phys. 74 (5)756–762, 2006.

    Google Scholar 

  3. Leemans, W. F., Janssen, H. L., and de Man, R. A., Future prospectives for the management of chronic hepatitis B. World J. Gastroenterol. 13 (18)2554–2567, 2007.

    Google Scholar 

  4. Weickert, U., Buttmann, A., Jakobs, R., Schilling, D., Eickhoff, A., and Riemann, J. F., Diagnosis of liver cirrhosis: a comparison of modified ultrasound and laparoscopy in 100 consecutive patients. J. Clin. Gastroenterol. 39 (6)529–532, 2005.

    Article  Google Scholar 

  5. Lefkowitch, J. H., Liver biopsy assessment in chronic hepatitis. Arch. Med. Res. 38 (6)634–643, 2007.

    Article  Google Scholar 

  6. Sebastiani, G., and Alberti, A., Non invasive fibrosis biomarkers reduce but not substitute the need for liver biopsy. World J. Gastroenterol. 12 (23)3682–3694, 2006.

    Google Scholar 

  7. Munteanu, M., Non-invasive biomarkers FibroTest-ActiTest for replacing invasive liver biopsy: the need for change and action. J. Gastrointestin. Liver Dis. 16 (2)173–174, 2007.

    Google Scholar 

  8. Dariani, S., Keshavarz, M., Parviz, M., Raoufy, M. R., and Gharibzadeh, S., Modeling force-velocity relation in skeletal muscle isotonic contraction using an artificial neural network. Biosystems. 90 (2)529–534, 2007.

    Article  Google Scholar 

  9. Tu, J. V., Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes. J. Clin. Epidemiol. 49:1225–1231, 1996.

    Article  Google Scholar 

  10. Hanley, J. A., and McNeil, B. J., The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 143:29–36, 1982.

    Google Scholar 

  11. Lok, A. S., and McMahon, B. J., Chronic hepatitis B: update of recommendations. Hepatology. 39:857–861, 2004.

    Article  Google Scholar 

  12. Chinese Society of Hepatology, Chinese Medical AssociationChinese Society of Infectious Diseases, Chinese Medical Association, Guideline on prevention and treatment of chronic hepatitis B in China (2005). Chin. Med. J. (Engl). 120 (24)2159–2173, 2007.

    Google Scholar 

  13. Haydon, G. H., Jalan, R., Ala-Korpela, M., Hiltunen, Y., Hanley, J., Jarvis, L. M., Ludlum, C. A., and Hayes, P. C., Prediction of cirrhosis in patients with chronic hepatitis C infection by artificial neural network analysis of virus and clinical factors. J. Viral. Hepat. 5 (4)255–264, 1998.

    Article  Google Scholar 

  14. Poon, T. C., Hui, A. Y., Chan, H. L., Ang, I. L., Chow, S. M., Wong, N., and Sung, J. J., Prediction of liver fibrosis and cirrhosis in chronic hepatitis B infection by serum proteomic fingerprinting: a pilot study. Clin. Chem. 51 (2)328–335, 2005.

    Article  Google Scholar 

  15. Piscaglia, F., Cucchetti, A., Benlloch, S., Vivarelli, M., Berenguer, J., Bolondi, L., et al., Prediction of significant fibrosis in hepatitis C virus infected liver transplant recipients by artificial neural network analysis of clinical factors. Eur. J. Gastroenterol. Hepatol. 18 (12)1255–1261, 2006.

    Article  Google Scholar 

  16. Swets, J. A., Measuring the accuracy of diagnostic systems. Science. 240:1285–1293, 1988.

    Article  MathSciNet  Google Scholar 

  17. Lin, C. S., Li, Y. C., Mok, M. S., Wu, C. C., Chiu, H. W., and Lin, Y. H., Neural network modeling to predict the hypnotic effect of propofol bolus induction. Proc. AMIA Symp. 450–454, 2002.

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Authors and Affiliations

  1. Department of Physiology, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran

    Mohammad Reza Raoufy & Parivash Eftekhari

  2. Department of Infectious Diseases, Logman Hospital, Tehran, Iran

    Parviz Vahdani

  3. Baqiyatallah Research Center for Gastroenterology and Liver Disease, Baqiyatallah University of Medical Sciences, Tehran, Iran

    Seyed Moayed Alavian

  4. Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran

    Sahba Fekri

  5. Neuromuscular Systems Laboratory, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

    Shahriar Gharibzadeh

Authors
  1. Mohammad Reza Raoufy
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  2. Parviz Vahdani
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  3. Seyed Moayed Alavian
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  4. Sahba Fekri
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  5. Parivash Eftekhari
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  6. Shahriar Gharibzadeh
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Corresponding author

Correspondence to Shahriar Gharibzadeh.

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Raoufy, M.R., Vahdani, P., Alavian, S.M. et al. A Novel Method for Diagnosing Cirrhosis in Patients with Chronic Hepatitis B: Artificial Neural Network Approach. J Med Syst 35, 121–126 (2011). https://doi.org/10.1007/s10916-009-9348-8

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  • DOI: https://doi.org/10.1007/s10916-009-9348-8

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