Harrison, R.F. and Kennedy, R. Lee (1990) The Multilayer Perceptron as an Aid to the Early Diagnosis of Myocardial Infarction. Research Report. Acse Report 395 . Dept of Automatic Control and System Engineering. University of Sheffield
Abstract
The establishment of a decision aid for the early diagnosis of myocardial infarction is described.The system uses a multi-layer Perceptron structure and is trained in the usual way. It is shown that the performance of the network can exceed that of the admitting clinicians, a panel of senior physicians in a large teaching hospital and a protocol derived using conventional statistical methods over a wide range of performance measures. In particular, the network demonstrates the highly specific behaviour necessary when making the decision whether or not to administer thrombolytic therapy-a potentially life-saving decision which must be taken in the very early stages, long before confirmatory laboratory test results are available. The network is compact and has been implemented on a portable computer. In operation it responds very quickly, giving its diagnosis and recommendations (taking account of clinical opinion) in a fraction of the time taken to input the patient's symptoms.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances. |
Keywords: | clinical decision support, myocardial infraction, chest pain, neural networks, connectionism, computer aided diagnosis. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports |
Depositing User: | MRS ALISON THERESA BARNETT |
Date Deposited: | 25 Mar 2014 12:03 |
Last Modified: | 31 Oct 2016 23:56 |
Status: | Published |
Publisher: | Dept of Automatic Control and System Engineering. University of Sheffield |
Series Name: | Acse Report 395 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:78277 |