Health Management & Information Science

Health Management & Information Science

Knowledge Acquisition for Diagnosis of Skin Diseases as an Initial Platform for an Expert System

Document Type : Articles

Authors
Fatemeh Rangraz Jeddi
Masoud Arabfard
Zahra Arab Kermani
Abstract
Background: The diagnosis of skin diseases, especially in patients suffering from more thanone disease or having similar symptoms, is very complex and access to the knowledge ofskin diseases makes the design of an expert system easier. This research aimed to design aknowledge base used for diagnosis of complex skin diseases, selected by experts.Methods: This applied developmental research was conducted in 2015. The studypopulation included 10 dermatologists of Razi Hospital, affiliated to Tehran University ofMedical Sciences. Data collection was conducted through a questionnaire and a checklist.The questionnaire had face and content validity and was based on Likert scale accordingto the twelfth chapter of the International Classification of Diseases (Tenth revision). Thequestionnaires were administered to participants and collected after completion. A checklistof knowledge acquisition was designed for each disease based on the semiology book of skindiseases with “agree-disagree” options and completed by interviews. Signs and symptoms had an agreement with at least 70% of the experts, and symptoms that were added according to the experts’ proposal entered the checklist and was given to experts for consensus in future evaluations. The software used in this research was Clementine and its statistical method used was Stata. The data were analyzed using SPSS, 16.Results: The diseases including pemphigus vulgaris, lichen planus, basal cell carcinoma,melanoma, and scabies were selected to design the expert system. Confirmed signs andsymptoms of the diseases selected by the experts included 106 causes.Conclusion: The choice of the selected diseases needed by specialists in the knowledgesystem is a very vital component needed in designing the expert knowledge base system tomeet international standards based on international classification and according to the needsof specialists.Keywords: Skin diseases, Knowledge acquisition, Knowledge base
  1. St Karagiannis A, Chalastras T, Tiropanis P,
  2. Papachristos D. Design of expert system for
  3. search allergy and selection of the skin tests using
  4. CLIPS. International Scholarly and Scientific
  5. Research & Innovation. 2007;1(7):461-4.
  6. Nourmohammadpour P, Ehsani AH, Esmaeili N,
  7. Gholamali F, Nourmohammadpour P.Emergency
  8. Dermatology A Rapid Treatment Guide. Tehran:
  9. Arjmand Publishen. 2013. [in Persian]
  10. Hay RJ, Johns NE, Williams HC, Bolliger IW,
  11. Dellavalle RP, Margolis DJ, et al. The global
  12. burden of skin disease in 2010: an analysis of the
  13. prevalence and impact of skin conditions. J Invest
  14. Dermatol. 2014;134(6):1527-34. doi: 10.1038/
  15. jid.2013.446
  16. Chen SC, Bayoumi AM, Soon SL, Aftergut K,
  17. Cruz P, Sexton SA, et al. A catalog of dermatology
  18. utilities: a measure of the burden of skin diseases.
  19. J Investig Dermatol Symp Proc. 2004;9(2):160-8.
  20. doi: 10.1046/j.1087-0024.2003.09112.x
  21. Naser SSA, Akilla A. A proposed expert system
  22. for skin diseases diagnosis. J Appl Sci Res.
  23. ;4(12):1682-93.
  24. Naser SSA, Ola AZA. An Expert System for
  25. Diagnosing Eye Diseases Using CLIPS. J Theor
  26. Appl Inf Technol. 2008;4(10):923-30.
  27. Sadeghzadeh M, rostami M, Afshari M,
  28. Chobdaran N. Designing Expert System to
  29. Diagnose and Suggest about Esophagus Cancer
  30. Treatment Method. National conference on
  31. computer and information technology, 2012 Feb
  32. , Kerman, Iran. [in Persian]
  33. Keleş A, Keleş A. ESTDD: Expert system for
  34. thyroid diseases diagnosis. Expert Syst Appl.
  35. ;34(1):242-6. doi: 10.1016/j.eswa.2006.09.028
  36. Tolouei AA, Mohsen TS. Designing an expert
  37. system for suggesting the blood cancer treatment.
  38. J Health Adm Educ. 2010;13(40):41-50.
  39. Durkin J, Durkin J. Expert systems: design and
  40. development. New Jersey: Prentice Hall PTR;
  41. Mortazavi H, Firooz A, Shahidi M. Textbook of
  42. dermatology for medical students and general
  43. practitioners. Tehran: Sepidbarg publication;
  44. [in Persian]
  45. Balighi K, Sobhanian Kh. Skin disease diagnosis
  46. and treatment. Tehran: Arjmand; 1998. [in
  47. Persian]
  48. Mansouri P, Mobasher P, Salavati A. Skin disease
  49. diagnosis and treatment. 2nd. Tehran: Rafi
  50. Andisheh Publication;2009[in Persian]
  51. Güvenir H, Emeksiz N. An expert system for the
  52. differential diagnosis of erythemato-squamous
  53. diseases. Expert Syst Appl. 2000;18(1):43-9. doi:
  54. 1016/s0957-4174(99)00049-4
  55. Al-Hajji A, editor Rule-Based expert system for
  56. diagnosis and symptom of neurological disorders
  57. “Neurologist Expert System (NES)”. Proceedings
  58. of the 1st Taibah University International
  59. Conference on Computing and Information
  60. Technology, Al-Madinah Al-Munawwarah,
  61. Saudi Arabia; 2012. p. 12-4.
  62. Ali SA, Saudi H. An expert system for the
  63. diagnosis and management of oral ulcers. Tanta
  64. Dental Journal. 2014;11(1):42-6. doi: 10.1016/j.
  65. tdj.2014.03.005
  66. Zolnoori M, Zarandi M, Moin M, Teimorian S.
  67. Designing fuzzy expert system for diagnosing
  68. and evaluating childhood asthma. Department
  69. of information technology management, Tarbiat
  70. Modares University Master of Science in
  71. Information Technology Management. 2007;199.
  72. Seto E, Leonard KJ, Cafazzo JA, Barnsley J,
  73. Masino C, Ross HJ. Developing healthcare
  74. rule-based expert systems: case study of a
  75. heart failure telemonitoring system. Int J
  76. Med Inform. 2012;81(8):556-65. doi: 10.1016/j.
  77. ijmedinf.2012.03.001
  78. Chu H-C, Hwang G-J. A Delphi-based
  79. approach to developing expert systems with
  80. the cooperation of multiple experts. Expert
  81. Syst Appl. 2008;34(4):2826-40. doi: 10.1016/j.
  82. eswa.2007.05.034
  83. Patra PSK, Sahu DP, Mandal I. An expert system
  84. for diagnosis of human diseases. Int J Comput
  85. Appl. 2010;1(13):71-3. doi: 10.5120/279-439
  86. Bucur S-M, Chibelean M, Gligor A, Pacurar
  87. M. Expert system for determining the level of
  88. stress before pediatric dental treatment. Procedia
  89. Technology. 2014;12:548-57. doi: 10.1016/j.
  90. protcy.2013.12.528
  91. Toki EI, Pange J, Mikropoulos TA. An online
  92. expert system for diagnostic assessment
  93. procedures on young children’s oral speech and language. Procedia Comput Sci. 2012;14:428-37.
  94. doi: 10.1016/j.procs.2012.10.049
  95. Maizels M, Wolfe WJ. An expert system
  96. for headache diagnosis: the Computerized
  97. Headache Assessment tool (CHAT).
  98. Headache. 2008;48(1):72-8. doi: 10.1111/j.1526-
  99. 2007.00918.x
  100. Alotaiby FA, Foda SG, editors. Chemical Threats
  101. Diagnosis Expert System (CTDES). Advanced
  102. Materials Research; 2012:396;1001-7. Trans Tech
  103. Publications.
Health Management & Information Science
Volume 5, Issue 2 - Serial Number 2
30
Spring 2018
Pages 41-50