Comparing Analytical Decision Support Models Through Boolean Rule Extraction: A Case Study of Ovarian Tumour Malignancy

Author:

Aung M. S. H.,Lisboa P. J. G,Etchells T. A.,Testa A. C.,Van Calster B.,Van Huffel S.,Valentin L.,Timmerman D.

Publisher

Springer Berlin Heidelberg

Reference6 articles.

1. Ameye, L.: Predictive Models for Classification in Gynecology. PhD thesis, Faculty of Engineering, Katholieke Universiteit Leuven, Leuven, Belgium (2005)

2. Aung, M.S.H., Lisboa, P.J.G., Taktak, A.F.G., Damato, B.E.: Modelling Survival of Intraocular Melanoma using a Partial Logistic Artificial Neural Network with Automatic Relevance Determination and Orthogonal Search Based Rule Extraction. In: Proc. Computational Intelligence in Medicine (CIMED), Lisbon, Portugal, pp. 114–121 (2005)

3. Van Calster, B., Timmerman, D., Nabney, I.T., Valentin, L., Van Holsbeke, C., Van Huffel, S.: Classifying Ovarian Tumors using Bayesian Multi-Layer Perceptrons and Automatic Relevance Determination: A Multi-Center Study. In: Proc. of the 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC2006), New York City, USA, pp. 5342–5345 (2006)

4. Etchells, T.A., Harrison, M.J.: Orthogonal Search-Based Rule Extraction for Modelling the Decision to Transfuse. Anesthesia 61(4), 335–338 (2006)

5. Etchells, T.A., Lisboa, P.J.G.: Orthogonal Search-Based Rule Extraction (OSRE) for Trained Neural Networks: A Practical and Efficient Approach. IEEE Trans Neur. Net. 17(2), 374–384 (2006)

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