In January 2010, the American Joint Committee on Cancer (AJCC) updated its staging criteria for uveal melanoma. Here, we discuss the staging classifications and evaluate an interesting case to demonstrate. The development of a uniform means of staging cancer, such as defined by the AJCC, is critical for information sharing among the research community.

We study the storage capacity of a fully-connected committee machine with a large number K of hidden nodes. The storage capacity is obtained by analyzing the geometrical structure of the weight space related to the internal representation . By examining the asymptotic behavior of order parameters in the limit of large K, the storage capacity Q c is found to be proportional to ]{ Jln ]{ up to th...

This article presents a defined classification of non-government community mental health services designed for reporting by the non-government sector. Initial classification involved review of the relevant literature, advisory committee consultation and content analysis of the Department of Health, Western Australia's service specifications and service contracts. A proposed classification was e...

OBJECTIVES To introduce abductive network classifier committees as an ensemble method for improving classification accuracy in medical diagnosis. While neural networks allow many ways to introduce enough diversity among member models to improve performance when forming a committee, the self-organizing, automatic-stopping nature, and learning approach used by abductive networks are not very cond...

This booklet has been prepared for an audience generally familiar with insurance concepts and terms but not necessarily with the technical aspects of insurance.

This paper demonstrates the use of abductive network classifier committees trained on different features for improving classification accuracy in medical diagnosis. In an earlier publication, committee members were trained on different subsets of the training set to ensure enough diversity for improved committee performance. In situations characterized by high data dimensionality, i.e. a large ...

Decision committee learning has demonstrated spectacular success in reducing classification error from learned classifiers. These techniques develop a classifier in the form of a committee of subsidiary classifiers. The combination of outputs is usually performed by majority vote. Voting, however, has a shortcoming. It is unable to take into account local expertise. When a new instance is diffi...