Prognostic systems for NPC: a comparison of the multi layer perceptron model and the recurrent model
Sameem Abdul Kareem, and Sapiyan Baba, and Yong Zulina Zubairi, and Prasad, U. and Mohd. Ibrahim A. Wahid, (2002) Prognostic systems for NPC: a comparison of the multi layer perceptron model and the recurrent model. In: Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference. ISBN: 981-04-7524-1, 18-22 November 2002.
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Official URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1202176
University of Malaya, Faculty of Computer Science & Information Technology
Artificial neural networks are considered good alternatives to conventional statistical methods for the prediction of survival. Neural networks have been used in medicine since the late 1980s, first, as an aid to diagnosis and treatment and then, recently, as a tool to study medical prognosis of a variety of diseases. Survival predictions at the individual level can help patients make informed decisions with regards to the quality of life and finance. We describe our research in the use of neural network to predict the prognosis of nasopharyngeal carcinoma. Two prognostic models for nasopharyngeal carcinoma were developed, namely the multi-layer perceptron model and the recurrent model and their performance compared.
|Item Type:||Conference or Workshop Item (Paper)|
|Keywords:||Artificial Neural network; nasopharyngeal carcinoma; Cancer|
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