Personalized decision support for rectal cancer patients
chinaCAT established an infrastructure to share patient data from multiple international institutions. This infrastructure will help to overcome the current administrative, political, ethical and technical barriers. Radiation treatment of rectum cancer patient’s generate large amounts of data. In this project, we used machine learning based on shared data to develop outcome prediction models. These models will provide personalized guidance and decision support for treatment of rectal cancer.
New outcome prediction models developed by machine learning and validated using European and Chinese oncology treatment data.
Distributed learning works and leads to meaningful clinical knowledge even when the data-sources are extremely different in terms of patient-population, language, culture and treatments.
After the chinaCAT ended, Fudan University joined the 20k challenge. Maastricht University and Fudan University maintain active research collaborations including joint PhD students.
|Funders||Varian Medical Systems|
Fudan University Shanghai Cancer Center, Shanghai, China / MAASTRO Clinic, Maastricht Netherlands / University of Pennsylvania, Philadelphia, PA, USA / Università Cattolica S Cuore, Rome, Italy