论文信息 - Self-organization with a large medical database: Using GTM for prediction and clustering - 字舞流文

Self-organization with a large medical database: Using GTM for prediction and clustering

We present an application of the Bishop’s GTM algorithm for the analysis of a large database of medical information and we explore a possible method to use the GTM for predictions.

David Lovell | Mahesan Niranjan | Richard W. Prager | R. Derom | B. Rosario | K. J. Dalton

[1] T. Kohonen. Self-organized formation of topographically correct feature maps , 1982 .

[2] T. Kohonen. Self-Organized Formation of Correct Feature Maps , 1982 .

[3] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[4] D R Lovell,et al. Design, construction and evaluation of systems to predict risk in obstetrics. , 1997, International journal of medical informatics.

[5] Christopher M. Bishop,et al. GTM: A Principled Alternative to the Self-Organizing Map , 1996, NIPS.

[6] J J Hopfield,et al. Learning algorithms and probability distributions in feed-forward and feed-back networks. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[7] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .