Complex Pattern Finding i Large Data Sets

In the later part of my PhD work I found that a bayesian recurrent neural network (a network using Bayesian logic and a frequentist approach to set the weights) which was originally invented by Anders Lansner and Örjan Ekeberg in the SANS group and has been improved by, Anders Holst and Anders Sandberg is an excellent tool to perform data mining in large data sets. To find patterns tremendously quick, due to the fact that it is working on global statistics. A method which has been succesfully applied to find syndromes in the WHO database.

This is published in the thesis I will soon provide a link to here, but due to the copyright rules and that the paper is in the publishing process I am not allowed, according the rules of today, to provide the actual paper.

The invention which I will present at this site before April 23rd 2004 builds upon this method which can be seen as applying AI in Medicine (AIM). I have extended this with another type of rule based reasoning into a method which will be applied to two other areas (which may also be abbreviated AIM). Two areas were researchers and geek thinking people are frustrated today, but where this invention will help to cure the reason for these symptoms which makes us frustrated.

Problems: (almost similar to the early warning problem) Last modified: Tue Mar 22 03:43:09 CEST 2002