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Medical AI systems as appropriate technology for developing countries

Published online by Cambridge University Press:  07 July 2009

Kathleen King
Affiliation:
Department of Artificial Intelligence, University of Edinburgh, UK
Howard Beck
Affiliation:
Artificial Intelligence Appications Institute, University of Edinburgh, UK

Abstract

Expert systems technology has been around for a long time, becoming increasingly easy to use, inexpensive and reliable in recent years. It would seem to provide an ideal vehicle for the dissemination of expertise in developing countries, particularly in the field of medicine, which was the focus of much early work in diagnostic systems. Despite the apparent match of a real problem and a credible solution, however, remarkably few AI systems for medicine in developing countries have been researched, designed and implemented. This paper addresses why this might be the case, reviews some of the extant systems and explores some of the design issues. Particular emphasis is placed on the question of “Appropriate Technology”. Various criteria for Appropriate Technology are explored, and an optimal set used to guide principles of design. It is argued that medical AI systems can satisfy these criteria, provided that sufficient care is taken in their design for the country of application.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1990

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References

Aegerter, P, Auvert, B, Gilbos, V, Desve, G, Benillouche, E, Landre, MF and Bos, D, 1987. “A computer-assisted instruction system designed for rural health workers in developing countries”. In: Proceedings of Conference on Medical Informatics in Europe 1987.Rome.Google Scholar
Auvert, B, Aegerter, P, Gilbos, V, Benillouche, E, Boutin, P, Desve, G, Landre, MF and Bos, D, 1986. “TROPICAID: a portable expert system for medical decision-aid in developing countries”. In: MEDINFO 86. Amsterdam: Elsevier Science Publishers.Google Scholar
Auvert, B, Aegerter, P, van Look, F, Huong-Du, LT, Boutin, P, Monier, JL, Emmanuelli, X, Gilbos, V and Benillouche, E, 1986. “A hand-held decision aid system designed for rural health workers. Computers and Biomedical Research 19.CrossRefGoogle ScholarPubMed
Briggs, BR, Lavett, SL, Pistorius, JG, van den Berg, ADP, Prax, M and de Klerk, JN. “SASEP a computerised diagnostic program”. Unpublished paper.Google Scholar
British Medical Association, 1985. Appropriate Technology: Articles from the British Medical Journal. London: British Medical Association.Google Scholar
Clancey, WJ and Shortliffe, EH, 1984. Readings in Medical Artificial Intelligence: The First Decade. Addison Wesley.Google Scholar
Eamsiri, J, Malasit, P, Songsivilia, S and Chongstitvatana, P, 1987. “Intelligent tutor for medical teaching”. In: Proceedings of the Regional Symposium on Computer Science and its Applications. Bangkok.Google Scholar
Eckhaus, RS, 1977. Applied Technology for Developing Countries. Washington DC: National Academy of Sciences. Prepared for the panel on Appropriate Technologies for Developing Countries.Google Scholar
Essex, BJ, 1980. Diagnostic Pathways in Clinical Medicine. Edinburgh: Churchill Livingstone.Google Scholar
Jequier, N and Blanc, G, 1979. Appropriate Technology Directory. Paris: OECD.Google Scholar
Kastner, JK, Dawson, CR, Weiss, SM, Kern, KB and Kulikowski, CA, 1984. “An expert consultation system for frontline health workers in primary eye care”. Journal of Medical Systems 8(5) 389397.CrossRefGoogle ScholarPubMed
Machanik, P, 1988. “Design of medical education software as appropriate technology using artificial intelligence and software engineering”. Technical Report 88–01. Johannesburg: University of the Witwatersrand.Google Scholar
Miller, RA, Pople, HE and Myers, JD, 1982. “INTERNIST-I: an experimental computer-based diagnostic consultant for general internal medicine”. New England Journal of Medicine 307(8).CrossRefGoogle ScholarPubMed
Ostroff, JH, Dawson, CR, Kastner, JK, Weiss, SM, Kulikowski, CA and Kern, KB, 1986. “Preliminary results from field testing of an expert advisory system for primary eye care in developing countries”. In: AI and Advanced Computer Technology, Proceedings of the 2nd Conference.Illinois:Wheaton.Google Scholar
Pankhurst, RJ, 1980. “Medical diagnosis in developing countries”. Computers in Biology and Medicine 10(69) 82.CrossRefGoogle ScholarPubMed
Perenta, G, Pfahringer, P, Hoberstorfer, M and Trappl, R, 1988. “A decision support system for village health workers in developing countries”. Applied Artificial Intelligence 2.Google Scholar
Quinlan, R, 1979. “Discovering rules from large sets of examples: a case study”. In: Michie, D (ed.), Expert Systems in the Microelectronic Age. Edinburgh: Elsevier Science Publishers.Google Scholar
Trappl, R and Horn, W, 1983. “Making interaction with a medical expert system easier”. In: MEDINFO 83. Amsterdam: Elsevier Science Publishers.Google Scholar
Uplekar, MW, Antia, NH and Dhumale, PS, 1988. “Sympmedl: computer program for primary health care”. British Medical Journal 297.CrossRefGoogle ScholarPubMed
WHO, 1978. “Primary health care: report on the international conference on primary health care”. Alma Ata USSR 1978. Health for All Series 1.Google Scholar
WHO Expert Committee, 1988. “Appropriate technology in the management of cardiovascular diseases”. Technical Report 772. Geneva: World Health Organisation.Google Scholar