We have collection of more than 1 Million open source products ranging from Enterprise product to
small libraries in all platforms. We aggregate information from all open source repositories.
Search and find the best for your needs. Check out projects section.
biorezonanta medicina bioresonance imaging scan dr. alexandru olga 0040723347034 biofeedback medical investigation with bioresonance . investigatii, diagnostic si tratament prin biorezonanta . http://www.medicinabiorezonanta.blogspot.com
Brunn is a laboratory information system for Bioclipse. It features a database model and a reference implementation for data from high-throughput drug screening and bioassays in cancer research. It features tools for management of microtiter plates.
Web application uses a C library from Collaborative Staging Task Force to enable convenient web interface for cancer staging. The application can be integrated into any existing web application and work in conjunction with exiting clinical data.
Website that when combined with a fitting R model will predict the survival time of a patient with lung cancer producing a graph and a table of the results. Technologies included are Java, JRI, rJava, R, and possibly JFreeChart.
Site em PHP para gerenciar as despesas dos pacientes da liga feminina de combate ao cancer. Contem: Cadastro de pacientes, RelaÃ§Ã£o das despesas, AutorizaÃ§Ã£o para gastos com pacientes, relatorios de despesas.
The aim of this project is to implement a realistic application of artificial neural networks. Our work will be based on wisconsin breast cancer database (http://mlearn.ics.uci.edu/databases/breast-cancer-wisconsin/) and use the C++-based Torch machine learning library to implement BackPropagation, EM with GMMs (initialized with the K-means algorithm) and an SVM algorithm.
Caisis is an open source web application designed to bridge the gap between Clinical Research and Clinical Practice. The application was originally designed to track data for Urologic cancer, but now has expanded to track a variety cancers and other medical conditions. The project was initiated with the goal of improving data quality and accuracy while reducing time and effort for clinicians and support staff. The Caisis team has openly embraced the open source model. As such, the application an