Data quality in a distributed learning environment

This project brings together academic, industrial and clinical leaders in a ‘Big-Data’ approach to improve cancer care. The project team will use, in a privacy preserving manner, vast amounts of data from thousands of patients from top cancer centres (for example MAASTRO and other national/international partners) to learn decision support systems (DSS) and demonstrate that these lead to better treatment decisions. The current network consists of 14 global partners from The Netherlands, Germany, Belgium, Italy, UK, Australia, China, USA and India.

The aim of this project is to further develop technology that enables global RLHC through local deployment, resulting in accurate, robust and actionable clinical DSS.

An important expected impact of this project is to induce a paradigm-shift, where healthcare professionals show increased acceptance of sophisticated ICT solutions in daily practice, and in particular predictive models and DSS. The field of Radiation Oncology is the ideal candidate to incite this necessary change, as the physicians in this field already make use of many ICT tools (for example visualization of anatomy/physiology/dose).

Project repository: https://github.com/maastroclinic/DataFAIRifier