Dr. Craig Niederberger's Research Interests

Dr. Niederberger's lab uses traditional statistical methods such as discriminant function analysis and logistic regression, as well as more novel methods such as neural networks and support vector machines, to model medical problems. Students from the University of Illinois at Chicago participate in their masters and doctoral theses, as well as medical students, residents and fellows. Completed and tested models are deployed for global physician use on handheld devices and the World Wide Web.

Students use a variety of computational methods to build models, including C++, Matlab, Perl, javascript and others. Application domains modelled include reproductive medicine, cancer, pediatric urology, nephrolithiasis and others. Deployed models may be found at http://www.urocomp.org.