Abstract
Non-invasive ultrasound imaging of carotid plaques allows for the development of plaque image analysis in order to assess the risk of stroke. In our work, we provide reliable confidence measures for the assessment of stroke risk, using the Conformal Prediction framework. This framework provides a way for assigning valid confidence measures to predictions of classical machine learning algorithms. We conduct experiments on a dataset which contains morphological features derived from ultrasound images of atherosclerotic carotid plaques, and we evaluate the results of four different Conformal Predictors (CPs). The four CPs are based on Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Naive Bayes classification (NBC), and k-Nearest Neighbours (k-NN). The results given by all CPs demonstrate the reliability and usefulness of the obtained confidence measures on the problem of stroke risk assessment.
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Belgaro, G., Nicolaides, A., Laurora, G., Cesarone, M., Sanctis, M.D., Incandela, L., Barsotti, A.: Ultrasound morphology classification of the arterial wall and cardiovascular events in a 6-year follow-up study. Arteriosclerosis, Thrombosis, and Vascular Biology 16(7), 851–856 (1996)
Nicolaides, A., Shifrin, E., Bradbury, A., Dhanjil, S., Griffin, M., Belcaro, G., Williams, M.: Angiographic and duplex grading of internal carotid stenosis: can we overcome the confusion? Journal of Endovascular Therapy 3(2), 158–165 (1996)
Papadopoulos, H.: Inductive conformal prediction, theory and application to neural networks. In: Fritzsche, P. (ed.) Tools in Artificial Intelligence, I-Tech., Vienna, Austria, pp. 315–330 (2008), http://intechweb.org/downloadpdf.php?id=5294
Proedrou, K., Nouretdinov, I., Vovk, V., Gammerman, A.: Transductive confidence machines for pattern recognition. In: Elomaa, T., Mannila, H., Toivonen, H. (eds.) ECML 2002. LNCS (LNAI), vol. 2430, pp. 381–390. Springer, Heidelberg (2002)
Saunders, C., Gammerman, A., Vovk, V.: Transduction with confidence and credibility. In: Proceedings of the 16th International Joint Conference on Artificial Intelligence, Los Altos, CA, vol. 2, pp. 722–726. Morgan Kaufmann, San Francisco (1999)
Vovk, V., Gammerman, A., Saunders, C.: Machine-learning applications of algorithmic randomness. In: Proceedings of the 16th International Conference on Machine Learning (ICML 1999), pp. 444–453. Morgan Kaufmann, San Francisco (1999)
Papadopoulos, H., Proedrou, K., Vovk, V., Gammerman, A.: Inductive confidence machines for regression. In: Elomaa, T., Mannila, H., Toivonen, H. (eds.) ECML 2002. LNCS (LNAI), vol. 2430, pp. 345–356. Springer, Heidelberg (2002)
Papadopoulos, H., Vovk, V., Gammerman, A.: Qualified predictions for large data sets in the case of pattern recognition. In: Proceedings of the 2002 International Conference on Machine Learning and Applications (ICMLA 2002), pp. 159–163. CSREA Press (2002)
Lambrou, A., Papadopoulos, H., Gammerman, A.: Evolutionary conformal prediction for breast cancer diagnosis. In: 9th International Conference on Information Technology and Applications in Biomedicine (ITAB 2009). IEEE, Los Alamitos (2009)
Papadopoulos, H., Gammerman, A., Vovk, V.: Confidence predictions for the diagnosis of acute abdominal pain. In: Iliadis, L., Vlahavas, I., Bramer, M. (eds.) Artificial Intelligence Applications & Innovations III. IFIP International Federation for Information Processing, vol. 296, pp. 175–184. Springer, Heidelberg (2009)
Bellotti, T., Luo, Z., Gammerman, A., Delft, F.W.V., Saha, V.: Qualified predictions for microarray and proteomics pattern diagnostics with confidence machines. International Journal of Neural Systems 15(4), 247–258 (2005)
Bellotti, T., Luo, Z., Gammerman, A.: Reliable classification of childhood acute leukaemia from gene expression data using confidence machines. In: Proceedings of IEEE International Conference on Granular Computing (GRC 2006), pp. 148–153 (2006)
Kyriacou, E., Pattichis, M.S., Pattichis, C.S., Mavrommatis, A., Christodoulou, C.I., Kakkos, S., Nicolaides, A.: Classification of atherosclerotic carotid plaques using morphological analysis on ultrasound images. Applied Intelligence 30(1), 3–23 (2009)
Langsfeld, M., Gray-Weale, A.C., Lusby, R.J.: The role of plaque morphology and diameter reduction in the development of new symptoms in asymptomatic carotid arteries. J. Vasc. Surg. 9, 548–557 (1989)
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Lambrou, A. et al. (2010). Assessment of Stroke Risk Based on Morphological Ultrasound Image Analysis with Conformal Prediction. In: Papadopoulos, H., Andreou, A.S., Bramer, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2010. IFIP Advances in Information and Communication Technology, vol 339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16239-8_21
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DOI: https://doi.org/10.1007/978-3-642-16239-8_21
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