Computer aided diagnostic problem solving: Identification of peripheral nerve disorders

IRBM

Volumn 34, Issue 3, 2013, Pages 244-251

  Kunhimangalam, R ^a   Ovallath, S ^b   Joseph, P K ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY CALICUT   (India)

^b Kannur Medical College   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTONOMIC NEUROPATHY; BRAIN COMPUTER INTERFACE; CARPAL TUNNEL SYNDROME; CLINICAL DECISION MAKING; COMPUTER ASSISTED DIAGNOSIS; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; DIFFERENTIAL DIAGNOSIS; ELECTRONIC MEDICAL RECORD; HUMAN; LATENT PERIOD; MAJOR CLINICAL STUDY; MATHEMATICAL MODEL; MOTOR NERVE CONDUCTION; NERVE CONDUCTION; PERIPHERAL NEUROPATHY; PREDICTIVE VALUE; PROBLEM SOLVING; SENSITIVITY AND SPECIFICITY; SENSORY NERVE CONDUCTION;

EID: 84878922720     PISSN: 19590318     EISSN: 18760988     Source Type: Journal    
DOI: 10.1016/j.irbm.2013.04.003     Document Type: Article

References (33)

1. B. Johnsen, and A. Fuglsang-Frederiksen Electrodiagnosis of polyneuropathy Neurophysiol Clin 30 6 2000 339 351
2. C. Krarup An update on electrophysiological studies in neuropathy Curr Opin Neurol 16 5 2003 603 612
3. I. Atroshi, C. Gummesson, R. Johnsson, E. Ornstein, J. Ranstam, and I. Rosen Prevalence of carpal tunnel syndrome in a general population JAMA 282 2 1999 153 158
4. J. Kimura Principles and pitfalls of nerve conduction studies Ann Neurol 16 4 1984 415 429
5. J. Kimura The carpal tunnel syndrome: localization of conduction abnormalities within the distal segment of the median nerve Brain 102 3 1979 619 635
6. A.N. Poncelet An algorithm for the evaluation of peripheral neuropathy Am Fam Physician 57 4 1998 755 764
7. E. Kiziltan, N. Dalkilic, F.B. Guney, and F. Pehlivan Conduction velocity distribution: early diagnostic tool for peripheral neuropathies Int J Neurosci 117 2 2007 203 213
8. H. Franssen, and P.Y. van den Bergh Nerve conduction studies in polyneuropathy: practical physiology and patterns of abnormality Acta Neurol Belg 106 2 2006 73 81
9. B.C. Cheah, and M.C. Kiernan Neurophysiological methodologies: diagnosis of peripheral nerve disease and assessment of pharmacological agents Curr Opin Investig Drugs 11 1 2010 72 79
10. R. Kunhimangalam, P.K. Joseph, and O.K. Sujith Nonlinear analysis of EEG signals: surrogate data analysis IRBM 29 4 2008 239 244
11. W.G. Baxt Application of artificial neural networks to clinical medicine Lancet 346 8983 1995 1135 1138
12. J.E. Dayhoff, and J.M. DeLeo Artificial neural networks: opening the black box Cancer 91 Suppl. 8 2001 1615 1635
13. A.X. Garg, N.K. Adhikari, H. McDonald, M.P. Rosas-Arellano, P.J. Devereaux, and J. Beyene Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review JAMA 293 10 2005 1223 1238
14. M. Suganthi, and M. Madheswaran An improved medical decision support system to identify the breast cancer using mammogram J Med Syst 36 1 2012 79 91
15. H. Tankisi, K. Pugdahl, B. Johnsen, and A. Fuglsang-Frederiksen Correlations of nerve conduction measures in axonal and demyelinating polyneuropathies Clin Neurophysiol 118 11 2007 2383 2392
16. C. Krarup Nerve conduction studies in selected peripheral nerve disorders Curr Opin Neurol 15 5 2002 579 593
17. F.J. Pineda Generalization of back-propagation to recurrent neural networks Phys Rev Lett 59 19 1987 2229 2232
18. E. Gelenbe Learning in the recurrent random neural network Neural Comput 5 1 1993 154 164
19. Xin Yao Evolving artificial neural networks P IEEE 87 9 1999 1423 1447
20. M.F. Moller A scaled conjugate gradient algorithm for fast supervised learning Neural Netw 6 4 1993 525 533
21. D.G. Altman, and J.M. Bland Diagnostic tests. 1: Sensitivity and specificity BMJ 308 6943 1994 1552
22. K. Wagholikar, V. Sundararajan, and A. Deshpande Modeling paradigms for medical diagnostic decision support: a survey and future directions J Med Syst 36 5 2012 3029 3049
23. T.J. Bright, A. Wong, R. Dhurjati, E. Bristow, L. Bastian, and R.R. Coeytaux Effect of clinical decision-support systems a systematic review Ann Intern Med 157 1 2012 29 43
24. K. Reeda, S. Ovallath, and P.K. Joseph Artificial neural networks in the identification of peripheral nerve disorders J Mech Med Biol 12 04 2012
25. K. Kawamoto, C.A. Houlihan, E.A. Balas, and D.F. Lobach Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success BMJ 330 7494 2005 765
26. E.H. Shortliffe Computer-based medical consultations: MYCIN 388 ed. 1976 Elsevier New York
27. R.A. Miller, H.E. Pople Jr., and J.D. Myers Internist-1, an experimental computer-based diagnostic consultant for general internal medicine N Engl J Med 307 8 1982 468 476
28. R.A. Miller Medical diagnostic decision support systems - past present, and future: a threaded bibliography and brief commentary J Am Med Inform Assoc 1 1 1994 8 27
29. Qeethara Kadhim, and Al-Shayea Artificial neural networks in medical diagnosis Int J Comput Sci Issues 8 2 2011 150 154
30. I. Anagnostopoulos, and I. Maglogiannis Neural network-based diagnostic and prognostic estimations in breast cancer microscopic instances Med Biol Eng Comput 44 9 2006 773 784
31. E. Orhan, F. Temurtas, and A. Tanrkulu Tuberculosis disease diagnosis using artificial neural networks J Med Syst 34 3 2010 299 302
32. B. Molnar, K. Papik, R. Schaefer, Z. Dombovari, J. Feher, and Z. Tulassay Medical use of artificial neural networks Orv Hetil 139 1 1998 3 9
33. D. Subha, Puthankattil, J.K. Paul, A.U. Rajendra, and C.M. Lim EEG signal processing: a survey J Med Syst 34 2 2010 195 212