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Automated Gentle Radiotherapy, Innovation, Standardisation and Availability

Reference number
Coordinator Region Västerbotten - Centrum för medicinsk teknik och strålningsfysik
Funding from Vinnova SEK 360 000
Project duration November 2018 - July 2019
Status Completed
Venture Challenge-Driven Innovation – Stage 1 initiation

Purpose and goal

The aim of the project is to develop products and services that give clinical staff a better ability to meet an increased need for cancer treatment. In step 1, the project has drawn up a plan to develop a national infrastructure for uniform collection of qualitative and efficient data and tools for securely sharing these, with the specific aim of jointly producing innovative decision support and automations.

Expected results and effects

The result is a national consortium with a concrete project plan and concrete performance goals for creating a national infrastructure within challenge-driven innovation, and with the help of needs owners and users, ensuring that it can produce large amounts of data appropriate for the development of machine learning prototypes for decision support and in the long term also automation of work tasks that today is done manually. The infrastructure will be developed to be l sustainable and also meet future data needs to continuously streamline the radiation treatment process.

Planned approach and implementation

The project has brought together all university clinics and a number of relevant companies operating in machine learning and radiation therapy to focus on needs inventory and to solve common problems to enable the development of innovative decision support and automation. This has resulted in a new consortium with a clear project plan and distribution of responsibilities that meet identified competence needs and clearly attack identified issues to achieve the project´s long-term objectives.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 31 October 2018

Reference number 2018-03353

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