Evaluation of inherent performance of intelligent medical decision support systems: utilising neural networks as an example.
Researchers who design intelligent systems for medical decision support, are aware of the need for response to real clinical issues, in particular the need to address the specific ethical problems that the medical domain has in using black boxes. This means such intelligent systems have to be thoroughly evaluated, for acceptability. Attempts at compliance, however, are hampered by lack of guidelines. This paper addresses the issue of inherent performance evaluation, which researchers have addressed in part, but a Medline search, using neural networks as an example of intelligent systems, indicated that only about 12.5% evaluated inherent performance adequately. This paper aims to address this issue by concentrating on the possible evaluation methodology, giving a framework and specific suggestions for each type of classification problem. This should allow the developers of intelligent systems to produce evidence of a sufficiency of output performance evaluation.
Smith
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AE
Medical Informatics, Faculty of Informatics, University of Ulster, Jordanstown, Newtownabbey, BT37 0QB, Northern Ireland, Antrim, UK. ae.smith@ulst.ac.uk
Nugent
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CD
McClean
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SI
D001185:Artificial Intelligence; D003658:Decision Making, Computer-Assisted; D020000:Decision Support Systems, Clinical; D015233:Models, Statistical; D016571:Neural Networks, Computer