From multisource data to clinical decision aids in radiation oncology: The need for a clinical data science community

Big data are no longer an obstacle; now, by using artificial intelligence (AI), previously undiscovered knowledge can be found in massive data collections. The radiation oncology clinic daily produces a large amount of multisource data and metadata during its routine clinical and research activities. These data involve multiple stakeholders and users. Because of a lack of interoperability, most of these data remain unused, and powerful insights that could improve patient care are lost. Changing the paradigm by introducing powerful AI analytics and a common vision for empowering big data in radiation oncology is imperative. However, this can only be achieved by creating a clinical data science community in radiation oncology. In this work, we present why such a community is needed to translate multisource data into clinical decision aids. (C) 2020 The Author(s). Published by Elsevier B.V

Professional development through mentoring : final evaluation of the pilot mentoring programme of the European society of radiotherapy and oncology

Abstract: The European SocieTy for Radiotherapy and Oncology (ESTRO) organized a one-year pilot mentoring programme. At evaluation after one year, both mentors and mentees scored the programme with a median score of 9 on a scale of 10. All of the mentors indicated that they wanted to participate again as mentors