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Methods Inf Med 1997; 36(02): 154-159
DOI: 10.1055/s-0038-1634708
Original Article
Schattauer GmbH

The Use of Knowledge-based Systems in Medicine in Developing Countries: A Luxury or a Necessity?

C. J. Tolmie
1   Department of Computer Science and Informatics, University of the Orange Free State, Bloemfontein, South Africa
,
J. P. du Plessis
1   Department of Computer Science and Informatics, University of the Orange Free State, Bloemfontein, South Africa
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Publication History

Publication Date:
20 February 2018 (online)

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Abstract:

Knowledge-based systems (KBSs) in medicine have received much attention over the past two decades, mainly because of the potential benefits that can be gained from using them. They may facilitate in increasing productivity in a medical environment, support the making of diagnoses and other types of medical decisions, assist in the training of medical professionals, and can even handle some routine tasks in a medical environment. However, some critical problems in this field have also been identified. For example, research indicated that some problems can be solved partially, but not completely, with existing artificial intelligence techniques. Another problem is that many of the existing medical information systems do not support the integration of KBSs in a natural way. Furthermore, the routine use of a medical KBS is complicated by legal issues. These and other problems contribute to what we experience today: a large proportion of the medical KB applications that are developed is never actually used in practice. This justifies questions such as: Should developing countries, having limited infrastructure and research resources, invest in medical KBSs research and development, or should this field be regarded as a luxury that only belongs to developed countries?, and: Can developing countries really benefit from the use of these systems? These questions are discussed in this paper. We highlight the main problems surrounding the development and use of medical KBSs. With the focus on developing countries we discuss potential benefits that could be obtained by investing in these systems and we offer guidelines for focusing research and development of medical KBSs.

Keywords:

Knowledge-based Systems - Developing Countries - Artificial Intelligence in Medicine
 

  • References

  • 1 Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ’90s?. Artif Intell Med 1993; 5: 93-106.
    CrossrefPubMedGoogle Scholar
  • 2 Green A. An introduction to health planning in developing countries. Oxford University Press; 1994
    Google Scholar
  • 3 Lee K, Mills A, Hoare G. Health economics research in developing countries: an overview. In: Mills A, Lee K. eds. Health Economics Research in developing countries. Oxford University Press; 1993: 1-16.
    Google Scholar
  • 4 Mäkelä M, Banerji D. Levels of health care. In: Lankinen KS, Bergström S, Mäkelä PH, Peltomaa M. eds. Health and diseases in developing countries. MacMillan; 1994: 393-401.
    Google Scholar
  • 5 Juva K, Mäkelä PH. Training of Health Workers. In: Lankinen KS, Bergström S, Mäkelä PH, Peltomaa M. eds. Health and diseases in developing countries. Macmillan; 1994: 427-32.
    Google Scholar
  • 6 Porenta G, Pfahringer B, Hoberstorfer M, Trappl R. A decision support system for village health workers in developing countries. In: Mann CK, Ruth SR. eds. Expert systems in developing countries: practice and promise. Westview Press; 1992: 193-207.
    Google Scholar
  • 7 Cibulskis RE. Knowledge-based systems for monitoring and evaluation of health services in developing countries. Lancet 1992; 33: 310.
    PubMedGoogle Scholar
  • 8 Bertrand WE. Information as a primary health care intervention: The impact of new technology on improving health for all. In: Wilson RG, Echols BE, Bryant JH, Abrantes A. eds. Management information systems and microcomputers in primary health care. Escola Nacional de Saude Publica; 1988: 21-6.
    Google Scholar
  • 9 Schware R. Management information systems and microcomputers in primary health care: Issues and challenges. In: Wilson RG, Echols BE, Bryant JH, Abrantes A. eds. Management information systems and microcomputers in primary health care. Escola Nacional de Saude Publica; 1988: 17-20.
    Google Scholar
  • 10 Bainbridge DI. Computer-aided diagnosis and negligence. Med Sci Law 1991; 2: 127-36.
    PubMedGoogle Scholar
  • 11 Monippallil M. The application of strict liability to defective expert systems. In: Turban E, Liebowitz J. eds. Managing expert systems. Idea Group Publishing; 1992: 211-28.
    Google Scholar
  • 12 Tolmie CJ. The Development of an expert system for the interpretation of complete blood count results at a private pathology firm. Ph. O. dissertation Bloemfontein: University of the Orange Free State; 1993
    Google Scholar
  • 13 Clayton PD, Hripesak G. Decision support in healthcare. Int J Biomed Comput 1995; 39: 59-66.
    CrossrefPubMedGoogle Scholar
  • 14 Wilson RG, Echols BE, Bryant JH, Abrantes A. eds. Management information systems and microcomputers in primary health care. Escola Nacional de Saude Publica; 1988
    Google Scholar
  • 15 Hedberg SR. Intelligent agents: The first harvest of softbots looks promising. IEEE Expert; 1995. August: 6–9.
    Google Scholar
  • 16 Weld DS, Marks J, Bobrow DG. eds. The role of intelligent systems in the national information infrastructure. AI Magazine 1995; Fall: 45-64.
    PubMedGoogle Scholar
  • 17 Bouche M, Plauchu V, Retour D. Troubleshooting expert systems for industrial maintenance: Pre-development guidelines. Expert Systems 1990; 3: 142-8.
    PubMedGoogle Scholar
  • 18 Mizoguchi R, Motoda H. Expert systems research in Japan. IEEE Expert; 1995. August: 14–23.
    Google Scholar
  • 19 Folley Jr JD, Hritz RJ. Embedded AI expert systems troubleshoots automated assembly. IE; 1987. April: 32–6.
    Google Scholar
  • 20 Powers L W. Diagnostic hematology: Clinical and technical principles. Mosby: 1989
    Google Scholar
  • 21 Burgess PR, Kershaw GW, Coleman RH, Robin H, Coad CD, Gibson J, Kronenberg H. A computerized expert system for handling the output of the technicon H1 haematology analyser. Clin Lab Haematol 1993; 15: 21-32.
    PubMedGoogle Scholar
  • 22 Kersten GE, Tolmie CJ. Artificial Intelligence: An overview of the field and its applications in medicine and health services. In: International Seminar on the Challenges of the Information Era: Agents and Users. Sao Paulo: 1994. (CD-ROM).
    Google Scholar
  • 23 Weghorst S. Virtual reality in medicine. Artif Intel in Med 1994; 6: 277-9.
    PubMedGoogle Scholar
  • 24 Kwa HY, van der Lei J, Kors JA. Expert systems integrated with information systems. Comput Methods Programs Biomed 1987; 25: 327-32.
    CrossrefPubMedGoogle Scholar
  • 25 Tolmie CJ, du Plessis JP. Embedding an expert system in a laboratory information system – experience with a real world application. In: Liebowitz J. Moving Towards Expert Systems Globally in the 21st Century. 1994. MacMillan; (CD-ROM).
    Google Scholar
  • 26 Harmon P, Sawyer B. Creating expert systems for business and industry. John Wiley & Sons, Inc.; 1990
    Google Scholar
  • 27 The intelligent software development tools market – Part L Intelligent Software Strategies. Cutter Information Corporation 1996; 2: 1-12.
    PubMedGoogle Scholar
  • 28 DeBrota DJ. In front of us. Int J Biomed Comput 1994; 34: 131-5.
    CrossrefPubMedGoogle Scholar
  • 29 Diamond LW, Mishka V, Seal AH, Nguyen D. Are normative expert systems appropriate for diagnostic pathology?. J Am Med Inform Assoc 1995; 2: 85-93.
    CrossrefPubMedGoogle Scholar
  • 30 Tolrnie CJ. The use of proto typing for the development of a system with both a knowledge-based component and a software-based component. Inform Decision Technol 1994; 19: 267-75.
    PubMedGoogle Scholar