Abstract
The objective of this paper is to assess the suitability of neural networks for the analysis of large medical data sets. For this purpose, we used an epidemiological data set from the Augsburg MONICA study (MONItoring trends and determinants in CArdiovascular diseases). The method of perception analysis and the interpretation of the model established by the network are explained. The results of a prediction of survival or death of patients who suffered acute myocardial infarction show that even simple perceptrons yield good classification quality. Further, the analysis of the connections within the neural network leads to information about relations between input and output data which are of interest for future epidemiological research. The results of these investigations can also be applied to other medical data sets like data on the segmentation of CTs and ECG data for the diagnosis of myocardial infarction.
Original language | English |
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Title of host publication | Artificial Intelligence in Medicine |
Editors | S. Andreassen, R. Engelbrecht, J. Wyatt |
Publisher | Publ by Elsevier Science Publishers B.V. |
Pages | 466-476 |
Number of pages | 11 |
Volume | 10 |
ISBN (Print) | 905199141X |
State | Published - 1993 |
Externally published | Yes |
Event | Proceedings of the 4th Conference on Artificial Intelligence in Medicine Europe - Munich, Ger Duration: 3 Oct 1993 → 6 Oct 1993 |
Conference
Conference | Proceedings of the 4th Conference on Artificial Intelligence in Medicine Europe |
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City | Munich, Ger |
Period | 3/10/93 → 6/10/93 |