A novel neural network-based survival analysis model
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Cluster Analysis for Gene Expression Data: A Survey
IEEE Transactions on Knowledge and Data Engineering
Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
ACM Transactions on Knowledge Discovery from Data (TKDD)
Double-blind evaluation and benchmarking of survival models in a multi-centre study
Computers in Biology and Medicine
Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding
SIAM Journal on Scientific Computing
Cluster-based visualisation with scatter matrices
Pattern Recognition Letters
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Clustering
Nonlinear Dimensionality Reduction
Nonlinear Dimensionality Reduction
IEEE Transactions on Neural Networks
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
An algorithm for finding gene signatures supervised by survival time data
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Severe sepsis mortality prediction with logistic regression over latent factors
Expert Systems with Applications: An International Journal
Cartogram visualization for nonlinear manifold learning models
Data Mining and Knowledge Discovery
Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours
Pattern Recognition Letters
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This article is not intended as a comprehensive survey of data mining applications in cancer. Rather, it provides starting points for further, more targeted, literature searches, by embarking on a guided tour of computational intelligence applications in cancer medicine, structured in increasing order of the physical scales of biological processes.