One of the industries that uses Machine Learning is Radiation Oncology
We welcome any use of this openData package. For any questions or inquiries please get in touch with filip.milojkovic .at. beenera.de
For a documentation of the content in GEM HOUSE openData please consult the paper. The scripts for generating an RData object and the paper can be accessed here as well (you may have to log in). Single file access is available on this web-frontend. For a more convenient access to data on the AWS S3 bucket you first need to register with IEEE free of charge (apply promotion code DATAPORT1, credit card details are necessary, please also consult the faq https://supportcenter.ieee.org/app/answers/detail/a_id/3187/kw/dataport). Log in to your account and renew your AWS credentials. Those can be used to download the full data via any AWS S3 client (such as cyberduck, cloudberry or cross ftp).
For convenient handling of this project, please download GEM-HOUSE-R-project.zip, which contains all code, text, data and graphs well sorted and ready to load into R-Studio (this does not include high-res data).