SOURCE-LINKED INTELLIGENCE

Twinning to skyrocket scientific excellence towards individual radiosensitivity prediction by raising the bar in knowledge transfer, networking, and technological innovation in radiobiology

CORDIS · observation · Publication date unknown

I), Germany, the University of Leicester (ULEIC), United Kingdom, Medical University of Vienna, Center for Cancer Research, (MUW) Austria, and the Institute of Oncology Ljubljana (IOL) from Slovenia. Artificial intelligence-based models, such as machine learning may give directions towards the clinical application of peripheral blood mononuclear cell transcriptome, and list potential biomarkers predicting radiotoxicity, not only in cancer patients, but also in healthy individuals at risk. RadExIORSBoost project may blaze the trail for technological innovations in modern radiation oncology to significantly reduce the side effects of RT and its harmful effects on the environment. Radiobiology, Individual radiosensitivity, Prostate cancer radiotherapy, Increase of IORS scientific excellence, Strengthening of IORS administrative capacity

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recordType

award

status

SIGNED

region

EU

value

1223641.27

unit

EUR