Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29207

Select areas to restrict search in scientific publication database:
An Intelligent Fuzzy-Neural Diagnostic System for Osteoporosis Risk Assessment
In this article, we propose an Intelligent Medical Diagnostic System (IMDS) accessible through common web-based interface, to on-line perform initial screening for osteoporosis. The fundamental approaches which construct the proposed system are mainly based on the fuzzy-neural theory, which can exhibit superiority over other conventional technologies in many fields. In diagnosis process, users simply answer a series of directed questions to the system, and then they will immediately receive a list of results which represents the risk degrees of osteoporosis. According to clinical testing results, it is shown that the proposed system can provide the general public or even health care providers with a convenient, reliable, inexpensive approach to osteoporosis risk assessment.
Digital Object Identifier (DOI):


[1] World Health Organization, "Assessment of fracture risk and its application to screening for postmenopausal osteoporosis," WHO, Geneva, Report series 843, 1994.
[2] C. Tudor Locke, and R. S. McColl, "Factors related to variation in premenopausal bone mineral status: a health promotion approach," Osteoporos-Int., vol. 11, no. 1, pp. 1-24, 2000.
[3] R. Bennett, "Bone mineral density tests: early diagnosis is prevention," Elder Update, vol. 10, no. 2, p. 2, 2000.
[4] J. Hansberger, "Osteoporosis: review of disease, diagnosis, and treatments for the advanced practice nurse," Int. Jour. of Adv. Nurs. Prac., vol. 8, no. 1, pp. 25-31, 2006.
[5] Ministry of the Interior, "Population Statistics in Taiwan," Aug. 2007; Available:
[6] N. Lavrac, "Selected techniques for data mining in medicine," Arti. Intell. in Med., vo. 16, pp. 3-23, 1999.
[7] R. Seising, "From vagueness in medical thought to the foundations of fuzzy reasoning in medical diagnosis," Arti. Intell. in Med., vol. 38, no. 3, pp. 237-256, 2006.
[8] E. D. Übeyli, and I. Güler, "Improving medical diagnostic accuracy of ultrasound Doppler signals by combining neural network models," Comp. in Bio. and Med., vol, 35, no. 6, pp. 533-554, 2005.
[9] S. Alay├│n, R. Robertson, S. K. Warfield, J. Ruiz-Alzola, "A fuzzy system for helping medical diagnosis of malformations of cortical development," Jour. of Bio. Inform., vol. 40, no. 3, pp. 221-235, 2007.
[10] K. Polat, and S. G├╝nes, "An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease," Digit. Sign. Proc., vol. 17, no. 4, pp. 702-710, 2007.
[11] L. S. Goggin, R. H. Eikelboom, and M. D. Atlas, "Clinical decision support systems and computer-aided diagnosis in otology," Otol. - Head and Neck Surgery, vol. 136, no. 4, pp. S21-S26, 2007.
[12] D. Ofluoglu, O. H. Gunduz, N. Bekirolu, E. Kul-Panza, and G. Akyuz, "A method for determining the grade of osteoporosis based on risk factors in postmenopausal women," Clin. Rheumatol., vol. 24, pp. 606-611, 2005.
[13] P. Povalej, M. Lenic, M. Zorman, P. Kokol, M. G. E. Peterson, J. M. Lane, "Intelligent data analysis of human bone density," Proc. 16th IEEE Symp. On Computer-based Medical Syst., pp. 397-402, 2003.
[14] S. D. Barnhill, and Z. Zhang, "Computer assisted methods for diagnosing diseases," US Patent 5,769,074, to Horus Therapeutics Inc., Patent and Trademark Office, 1998.
[15] S. D. Barnhill, and Z. Zhang, "Computer assisted methods for diagnosing diseases," US Patent 6,248,063, to Horus Therapeutics Inc., Patent and Trademark Office, 2001.
[16] E. Binaghi, O. De Giorgi, G. Maggi, T. Motta, and A. Rampini, "Computer-assisted diagnosis of postmenopausal osteoporosis using a fuzzy expert system shell," Comp. and Biom. Res., vol. 26, no. 6, pp. 498-516, 1993.
[17] M. F. Sturman, "EasyDiagnosis Expert System Programs," Mar. 2007; Available:
[18] C. T. Lin, "A neural fuzzy control system with structure and parameter learning," Fuzzy Sets and Syst., vol. 70, pp. 183-212, 1995.
[19] R. Babuška, Fuzzy Modeling for Control. Norwell, Massachusetts: Kluwer Academic Publishers, 1998.
[20] R. P. Paiva and A. Dourado, "Interpretability and learning in neuro-fuzzy systems," Fuzzy Sets Sys., vol. 147, pp. 17-38, 2004.
[21] D. Nauck and R. Kruse, "Obtaining interpretable fuzzy classification rules from medical data," Artif. Intell. in Med., vol. 16, pp.149-169, 1999.
[22] C. M. Hong, C. M. Chen, S. Y. Chen, and C. Y. Huang, "A novel and efficient neuro-fuzzy classifier for medical diagnosis," Inter. Joint Conf. on Neur. Net., IJCNN-06, pp. 735-741, 2006.
[23] C. M. Hong, and C. Y. Huang, "Tele-homecare system: medical diagnostic system (II)," National Science Council, Tech. Rep. NSC 94-2218-E-003-001, 2006.
Vol:13 No:01 2019
Vol:12 No:12 2018Vol:12 No:11 2018Vol:12 No:10 2018Vol:12 No:09 2018Vol:12 No:08 2018Vol:12 No:07 2018Vol:12 No:06 2018Vol:12 No:05 2018Vol:12 No:04 2018Vol:12 No:03 2018Vol:12 No:02 2018Vol:12 No:01 2018
Vol:11 No:12 2017Vol:11 No:11 2017Vol:11 No:10 2017Vol:11 No:09 2017Vol:11 No:08 2017Vol:11 No:07 2017Vol:11 No:06 2017Vol:11 No:05 2017Vol:11 No:04 2017Vol:11 No:03 2017Vol:11 No:02 2017Vol:11 No:01 2017
Vol:10 No:12 2016Vol:10 No:11 2016Vol:10 No:10 2016Vol:10 No:09 2016Vol:10 No:08 2016Vol:10 No:07 2016Vol:10 No:06 2016Vol:10 No:05 2016Vol:10 No:04 2016Vol:10 No:03 2016Vol:10 No:02 2016Vol:10 No:01 2016
Vol:9 No:12 2015Vol:9 No:11 2015Vol:9 No:10 2015Vol:9 No:09 2015Vol:9 No:08 2015Vol:9 No:07 2015Vol:9 No:06 2015Vol:9 No:05 2015Vol:9 No:04 2015Vol:9 No:03 2015Vol:9 No:02 2015Vol:9 No:01 2015
Vol:8 No:12 2014Vol:8 No:11 2014Vol:8 No:10 2014Vol:8 No:09 2014Vol:8 No:08 2014Vol:8 No:07 2014Vol:8 No:06 2014Vol:8 No:05 2014Vol:8 No:04 2014Vol:8 No:03 2014Vol:8 No:02 2014Vol:8 No:01 2014
Vol:7 No:12 2013Vol:7 No:11 2013Vol:7 No:10 2013Vol:7 No:09 2013Vol:7 No:08 2013Vol:7 No:07 2013Vol:7 No:06 2013Vol:7 No:05 2013Vol:7 No:04 2013Vol:7 No:03 2013Vol:7 No:02 2013Vol:7 No:01 2013
Vol:6 No:12 2012Vol:6 No:11 2012Vol:6 No:10 2012Vol:6 No:09 2012Vol:6 No:08 2012Vol:6 No:07 2012Vol:6 No:06 2012Vol:6 No:05 2012Vol:6 No:04 2012Vol:6 No:03 2012Vol:6 No:02 2012Vol:6 No:01 2012
Vol:5 No:12 2011Vol:5 No:11 2011Vol:5 No:10 2011Vol:5 No:09 2011Vol:5 No:08 2011Vol:5 No:07 2011Vol:5 No:06 2011Vol:5 No:05 2011Vol:5 No:04 2011Vol:5 No:03 2011Vol:5 No:02 2011Vol:5 No:01 2011
Vol:4 No:12 2010Vol:4 No:11 2010Vol:4 No:10 2010Vol:4 No:09 2010Vol:4 No:08 2010Vol:4 No:07 2010Vol:4 No:06 2010Vol:4 No:05 2010Vol:4 No:04 2010Vol:4 No:03 2010Vol:4 No:02 2010Vol:4 No:01 2010
Vol:3 No:12 2009Vol:3 No:11 2009Vol:3 No:10 2009Vol:3 No:09 2009Vol:3 No:08 2009Vol:3 No:07 2009Vol:3 No:06 2009Vol:3 No:05 2009Vol:3 No:04 2009Vol:3 No:03 2009Vol:3 No:02 2009Vol:3 No:01 2009
Vol:2 No:12 2008Vol:2 No:11 2008Vol:2 No:10 2008Vol:2 No:09 2008Vol:2 No:08 2008Vol:2 No:07 2008Vol:2 No:06 2008Vol:2 No:05 2008Vol:2 No:04 2008Vol:2 No:03 2008Vol:2 No:02 2008Vol:2 No:01 2008
Vol:1 No:12 2007Vol:1 No:11 2007Vol:1 No:10 2007Vol:1 No:09 2007Vol:1 No:08 2007Vol:1 No:07 2007Vol:1 No:06 2007Vol:1 No:05 2007Vol:1 No:04 2007Vol:1 No:03 2007Vol:1 No:02 2007Vol:1 No:01 2007