Neural Expert Systems in Medical Image Interpretation: Development, Use, and Ethical Issues

In this paper, the appropriate level and role of neural network-based methodologies in the development and use of expert systems for medical image interpretation is investigated as technical, organizational, and social issues become intertwined. The notion of the information life cycle is applied to highlight ethical issues during the acquisition, processing and storage, dissemination and use of clinical information. These issues are further analyzed from a stakeholder perspective to accentuate the role of human agents in avoiding ethical risks. Relevant stakeholders, other than the key participants—namely system developers and medical users—are identified. The results of this analysis indicate that each stage of the development and use of a neural expert system entails ethical issues. Significantly, the responsibility for medical image interpretation is affected by contextual factors and should be shared amongst the main stakeholders. These conclusions are useful for the stakeholder groups that are conscious of their obligation to behave ethically and for researchers who wish to investigate further the ethical implications of artificial intelligence use in medicine. tel.: +44-1895-274000 ext. 3745, 2521; fax: +44-1895-251686 e-mail: {Nancy.Pouloudi, George.Magoulas}@brunel.ac.uk

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