Medical diagnosis using adaptive perceptive particle swarm optimization and its hardware realization using field programmable gate array

Journal of Medical Systems

Volumn 33, Issue 6, 2009, Pages 447-465

  Roy Chowdhury, Shubhajit ^a   Chakrabarti, Dipankar ^b   Saha, Hiranmay ^a  

^a JADAVPUR UNIVERSITY   (India)

^b Om HealthNet Telemedicine Private Limited   (India)

Author keywords

Adaptive perceptive particle swarm optimization; Criticality; Field programmable gate array; Medical diagnosis

Indexed keywords

CREATININE; GLUCOSE; UREA;

ARTICLE; BODY MASS; CONTROLLED STUDY; DECISION SUPPORT SYSTEM; DEVELOPING COUNTRY; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; DIASTOLIC BLOOD PRESSURE; HEALTH CARE FACILITY; IMAGING SYSTEM; MATHEMATICAL MODEL; SENSITIVITY AND SPECIFICITY; SYSTOLIC BLOOD PRESSURE;

ALGORITHMS; DIAGNOSIS, COMPUTER-ASSISTED; FUZZY LOGIC; HUMANS; KIDNEY DISEASES; PATTERN RECOGNITION, AUTOMATED;

EID: 70350230303     PISSN: 01485598     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10916-008-9206-0     Document Type: Article

References (60)

1. M. Kukar 2003 Transductive reliability estimation in medical diagnosis Artif. Intell. Med. 29 81 106 doi:10.1016/S0933-3657(03)00043-5. (Pubitemid 37072093)
2. Indian Medical Society, Technical report of technical working group on telemedicine standardization. Technical Report, Indian Medical Society, May 2003.
3. Rural Community Development Program, http://www.rcdpnepal.com/india/ india-health-sector.php
4. A. Eren A. Subasi O. Coskun 2008 A decision support system for telemedicine through the mobile telecommunications platform J. Med. Syst. 32 1 31 35 doi:10.1007/s10916-007-9104-x.
5. U. Fidan N. F. Guler 2007 A four channel biotelemetry system employing indoor J. Med. Syst. 31 3 159 165 doi:10.1007/s10916-006-9029-9. (Pubitemid 46985757)
6. S. Walczak 2003 A multiagent architecture for developing medical information retrieval agents J. Med. Syst. 27 5 479 498 doi:10.1023/A: 1025668124244 (Pubitemid 38115307)
7. C. E. Kuziemsky F. Laul F. C. Leung 2005 A review on diffusion of personal digital assistants in healthcare J. Med. Syst. 29 4 335 342 doi:10.1007/s10916-005-5893-y (Pubitemid 41203638)
8. M. Hashiba T. Matsuto F. Arai T. Yamakawa K. Azakawa 2000 Accessing endoscopic images for remote conference and diagnosis using WWW server with a secure socket layer J. Med. Syst. 24 6 333 338 doi:10.1023/A:1005596610165. (Pubitemid 32002814)
9. M. Druzovec T. Welzer B. Brumen 2005 Agent oriented approach to handling medical data J. Med. Syst. 29 1 45 57 doi:10.1007/s10916-005-1103-1. (Pubitemid 40386106)
10. R. A. Neill A. G. Mainous J. R. Clark M. D. Hagen 1994 The utility of electronic mail as a medium for patient-physician communication Arch. Fam. Med. 3 268 271 doi:10.1001/archfami.3.3.268.
11. P. A. Halvorsen I. S. Kristiansen 1996 Radiology services for remote communities: cost minimisation study of telemedicine Biom. J. 312 3 1333 1336
12. Fery-Lemonnier, E., Brayda, F., Charpentier, E., Couturon, I., Fay, A., and Souag, A., Transmission interhospitaliere d'images radiologiques pour la prise en charge des urgences neurochirurgicales Resultats de l'evaluation. Comité d'Evaluation et de Diffusion des Innovations Technologiques (CEDIT), Paris, 1996.
13. J. E. Bailes C. C. Poole W. Hutchison J. C. Maroon T. Fukushima 1997 Utilization and cost savings of a wide-area computer network for neurosurgical consultation J. Telemed. 3 135 139
14. K. Y. C. Goh C. K. Lam W. S. Poon 1997 The impact of teleradiology on the inter-hospital transfer of neurosurgical patients Br. J. Neurosurg. 11 52 56 doi:10.1080/02688699746708. (Pubitemid 27086953)
15. J. F. Heautot B. Gibaud B. Catroux P. H. Thoreux E. Cordonnier J. M. Scarabin 1999 Influence of the teleradiology technology (N-ISDN and ATM) on the inter-hospital management of neurosurgical patients Med. Inform. (Lond.) 24 121 134
16. Hailey, D., and Jacobs, P., Assessment of telehealth applications. Alberta Heritage Foundation for Medical Research, Edmonton (Alta), 1997.
17. R. Wootton 1996 Telemedicine: a cautious welcome J. Biomed. 313 1375 1377
18. R. M. Brecht C. L. Gray C. Peterson B. Youngblood 1996 The University of Texas Medical Branch-Texas Department of Criminal Justice Telemedicine Project: findings from the first year of operation J. Telemed. 2 25 35
19. M. J. McCue P. E. Mazmanian C. Hampton T. K. Marks E. Fisher F. Parpart 1997 The case of Powhatan Correctional Center/Virginia Department of Corrections and Virginia Commonwealth University/Medical College of Virginia J. Telemed. 3 1 11 17
20. W. J. Crump R. J. Tessen 1997 Communication in integrated practice networks: using interactive video technology to build the medical office without walls Tex. Med. Inform. 93 70 74
21. A. M. House J. M. Roberts 1977 Telemedicine in Canada Can. Med. Assoc. J. 117 4 386 388
22. R. L. Murphy K. T. Bird 1974 Telediagnosis: a new community health resource; observations on the feasibility of telediagnosis based on 1000 patient transactions Am. J. Public Health 64 2 113 119
23. R. L. Murphy T. B. Fitzpatrick H. A. Haynes K. T. Bird T. B. Sheridan 1972 Accuracy of dermatologic diagnosis by television Arch. Dermatol. 105 6 833 835 doi:10.1001/archderm.105.6.833.
24. D. S. Watson 1989 Telemedicine Med. J. Aust. 151 2 62 66
25. Davis, J. G., Final report: Video requirements for remote medical diagnosis. Southern Hospice Foundation, Inc., Houston, 1974.
26. Li, J., and Wong, L., Using rules to analyze biomedical data: comparison between C4.5 and PCL. Institute for Infocomm Research, Singapore, 2003Technical Report.
27. Ghennad Rezaie, M., Soltanain-Zadeh, H., Siadat, M. R., and Elisevich, K. V., Medical Data Mining using Particle Swarm Optimization for Temporal Lobe Epilepsy. Proceedings of IEEE Congress on Evolutionary Computation, Vancouver Canada, IEEE Press, Vol. 1447, pp. 761-768, 2006 (Edited by: Garg G. Yen, Simon M. Lucas, Gary Fogel, Graham Kendell, Ralf Solomon, Byoung Tak Zhang, Carlos A. Coello, Thomas Philip Runarssen).
28. Larranaga, P., Learning Bayesian networks from data: some applications in biomedicine. Intelligent System Group, Department of Computer Science and Artificial Intelligence, University of Basque, Basque, 2002technical report.
29. J. I. Kazi P. N. Furness M. Nicholson E. Ahmed F. Akhter A. Naqvi, et al. 1999 Interinstitutional variation in the performance of Bayesian belief network for the diagnosis of acute renal graft rejection Transplant. Proc. Elsevier 31 8 31 52 Editor: Barry D. Kahan.
30. Keneddy, J., The behavior of particles. In: William Porto, V., Saravanan, N., Waagen, D. E., and Eiben, A. E. (Eds.), Proceedings of Evolutionary Programming ConferenceVol. 8. Springer, London, pp. 32-37, 1998.
31. Bäck, T., Fogel, D., and Michalewicz, Z., Handbook of Evolutionary Computation. IOP Publishing and Oxford University Press, New York, 1997.
32. Schwefel, H.-P., Evolution and optimum seeking. Wiley, New York, 1995.
33. Kennedy, J., and Ebarhart, R. C., Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks November 27-December 1, Perth, Australia, IEEE Service Centre, Piscataway, New Jersey, Vol. 4, pp. 1942-1948, 1995.
34. Gott, M., Telematics for health: the role of telemedicine in homes and communities. Radcliffe Med. Press, Oxford, 1995.
35. M. A. Abido 2002 Optimal design of power system stabilizers using particle swarm optimization IEEE Trans. Energ. Convers. 17 3 406 413 doi:10.1109/TEC.2002.801992. (Pubitemid 35151678)
36. D. K. Agrafiotis W. Cedeno 2002 Feature selection for structure-activity correlation using binary particle swarms J. Med. Chem. 45 5 1098 1107 doi:10.1021/jm0104668. (Pubitemid 34173920)
37. C. Fourie A. A. Groenwold 2002 The particle swarm optimization algorithm in size and shape optimization Struct. Multidisciplinary Optim. 23 259 267 doi:10.1007/s00158-002-0188-0. (Pubitemid 35354676)
38. C. O. Ourique E. C. Biscaia J. Carlos Pinto 2002 The use of particle swarm optimization for dynamical analysis in chemical processes Comput. Chem. Eng. 26 1783 1793 doi:10.1016/S0098-1354(02)00153-9. (Pubitemid 35303615)
39. K. E. Parsopoulos M. N. Vrahatis 2002 Recent approaches to global optimization problems through particle swarm optimization Nat. Comput. 1 2-3 235 306 1018.68063 doi:10.1023/A:1016568309421.
40. K. E. Parsopoulos M. N. Vrahatis 2004 On the computation of all global minimizers through particle swarm optimization IEEE Trans. Evol. Comput. 8 3 211 224 doi:10.1109/TEVC.2004.826076.
41. K. E. Parsopoulos E. I. Papageorgiou P. P. Groumpos M. N. Vrahatis 2004 Evolutionary computation techniques for optimizing fuzzy cognitive maps in radiation therapy systems Lect. Notes Comput. Sci. 3102 402 413
42. K. E. Parsopoulos M. N. Vrahatis 2005 Unified particle swarm optimization in dynamic environments Lect. Notes Comput. Sci. 3449 590 599
43. T. Ray K. M. Liew 2002 A swarm metaphor for multiobjective design optimization Eng. Optim. 34 2 141 153 doi:10.1080/03052150210915. (Pubitemid 35263146)
44. Parsopoulos, K. E., and Vrahatis, M. N., UPSO: A unified particle swarm optimization scheme. Proceedings of the International Conference of Computational Methods in Sciences and Engineering ICCMSE 2004, Lecture Series on Computer and Computational Sciences Vol. 1, VSP International Science Publishers, Zeist, The Netherlands, pp. 868-873, 2004.
45. K. E. Parsopoulos M. N. Vrahatis 2007 Parameter selection and adaptation in Unified Particle Swarm Optimization Math. Comput. Model. 46 1-2 198 213 1149.90432 doi:10.1016/j.mcm.2006.12.019. (Pubitemid 46660521)
46. R. Kathiravan R. Ganguli 2007 Strength design of composite beam using gradient and particle swarm optimization Compos. Struct. 81 4 471 479
47. S. Suresh P. B. Sujit A. K. Rao 2007 Particle swarm optimization approach for multi-objective composite box-beam design Compos. Struct. 81 4 598 605 doi:10.1016/j.compstruct.2006.09.007. (Pubitemid 46958967)
48. H. Feng C. Chen F. Ye 2007 Evolutionary fuzzy particle optimization vector quantization learning in image compression Expert Syst. Appl. 32 213 222 doi:10.1016/j.eswa.2005.11.012. (Pubitemid 44311478)
49. Bonabeau, E., Dorigo, M., and Théraulaz, G., From natural to artificial swarm intelligence. Oxford University Press, New York, 1999.
50. Kennedy, J. and Eberhart, R. C., Swarm Intelligence, Morgan Kaufmann. 2001.
51. Kaewkamnerdpong, B., and Bentley, P., Perceptive Particle Swarm Optimization: An investigation. Proc. IEEE Symp. Swarm Intell. IEEE CS Press 1(1), 8-10 (2005)
52. A. Saldam I. Ahmad S. Al-Madani 2002 Particle swarm optimization for task assignment problem Microprocess. Microsyst 26 363 371 doi:10.1016/S0141- 9331(02)00053-4. (Pubitemid 35049027)
53. Xiaohui, H., Eberhart, R. C., and Yuhui, S., Particle Swarm with extended memory for multiobjective optimization. Proc. IEEE Swarm Intell. Symp. Indianap. USAIEEE Press 1, 193-197 (2003)
54. S. Roy Chowdhury D. Chakrabarti H. Saha 2008 FPGA realization of a Smart Processing System for Clinical Diagnostic Applications using Pipelined Datapath Architectures Microprocess. Microsyst. 32 2 107 120 doi:10.1016/j.micpro.2007. 12.001.
55. Gibbs, A. L., and Braunwald, E., Primary cardiology. Saunders: Philadelphia, 1998.
56. Kasper, D. L., Braunwald, E., Hauser, S., Longo, D., Jameson, J. L., and Fauci, A. S., Harrison's Principle of Internal Medicine, 16th edition. McGraw Hill, New York, 2008.
57. Gibbs, A. L., and Braunwald, E., Primary cardiology. Saunders, Philadelphia, 1998.
58. Olona-Cabases, M., The probability of a correct diagnosis. In: Candell-Riera, J., and Ortega-Alcalde, D. (Eds.), Nuclear Cardiology in Everyday Practice348-357, 1994.
59. Lee, K. H., A first course on fuzzy theory and application. Springer Verlag, Germany, 2005.
60. Fletcher, B. H., FPGA embedded processors: revealing true system performance. Proceedings of Embedded System Conference, Vol. 1, No. 1, pp 11-31, San Francisco, 2005