Abstract
To evaluate some intelligent method for decision-making we need to compare the method against the competing methods to get some idea of its performance and capabilities. In everyday practice this is enough and the method, if proven good, can be used for different problems. In medicine however we have a demand for the best solution in all circumstances. It is therefore impossible to declare one method as acceptable for every type or even every single problem. In this article we would like to stress some important aspects of machine learning in medicine, especially the creation of specific decision models. We believe the evolutionary concept is a good approach to this as it creates many diverse solutions.
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References
A Second Opinion Medical, An Information & Physician Verification Service: http://www.physicians-background.com (jan. 2001)
Banzhaf, W., Nordin, P., Keller, R. E., Francone, F. D.: Genetic Programming — An Introduction. Morgan Kaufmann Publishers Inc (1998)
Boudoulas, H., Kolibash, A. J., Baker, P., King, B. D., Wooley, C. F.: Mitral Valve Prolapse and the Mitral Valve Prolapse Syndrome: A Diagnostic Classification and Pathogenesis of Symptoms. American Heart Journal, 118 (1989), 796–818
Kokol, P. Et al: Decision Trees and Automatic Learning and their Use in Cardiology. Journal of Medical Systems. 19(4) (1994)
Podgorelec, V., Kokol, P.: Self-Adaptation of Evolutionary Constructed Decision Trees by Information Spreading. Proceedings of the International Conference on Artificial Neural Nets and Genetic Algorithms. Springer Verlag (1999) 294–301
Quinlan, J. R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA (1993)
UCI Machine Learning: http://www.ics.uci.edu/~mlearn/Machine-Learning.html (feb. 2001)
Wolpert, D., Macready, W.: No Free Lunch Theorems for Optimization. IEEE Transactions on Evolutionary Computation, Vol. 1(1) (1997) 67–82
Yale-New Haven Hospital: Getting a Good Second Opinion. http://www.ynhh.org (2001)
Šprogar, M., Kokol, P., Hleb Babič, Š., Podgorelec, V., Zorman, M.: Vector Decision trees. Intelligent Data Analysis 4, IOS Press (2000) 305–321
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Šprogar, M., Kokol, P., Zorman, M., Podgorelec, V., Lhotska, L., Klema, J. (2001). Notes on Medical Decision Model Creation. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_41
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DOI: https://doi.org/10.1007/3-540-45497-7_41
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