Reference to article on Neural Nets for cancer diagnosis

[sontag@control.rutgers.edu]

People in this list may be interested in reading the latest (September) SIAM
News.  The leading front-page article is about cancer diagnosis via neural
nets (the title says "linear programming", but the text explains the relation
to nn's).  The method appears to be extremely succesful, almost 100% accurate
for breast cancer.  An outline of the algorithm is as follows (as I understood
it from the article): if the data is not linearly separable, then first
sandwich the intersection of the convex hulls of the training data between two
hyperplanes.  Ignore the rest (already separated), restrict to this sandwich
region, and iterate.  The authors prove (in the references) that this gives a
polynomial time algorithm (essentially using LP for each sandwich
construction; the "size" is unclear), presumably under the assumption that a
polyhedral boundary exists.  The references are to various papers in SIAM
publications and IEEE/IT.  The authors are Olvi L. Mangasarian
(olvi at cs.wisc.edu) from the Math and CS depts at Madison, and W.H. Wolberg
from the Wisconsin medical school.

-eduardo