Aerts Lab

Maastricht University

Zuid-Nederland (NL4) · Netherlands

ERC-funded
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ERC Consolidator Grant · 2019

Deep Learning for Automated Quantification of Radiographic Tumor Phenotypes

Artificial Intelligence (AI), deep-learning in particular, is propelling the field of radiology forward at a rapid pace. In oncology, AI can characterize the radiomic phenotype of the entire tumor and provide a non-invasive window into the internal growth patterns of a cancer lesion. This is especially important for patients treated with immunotherapy as, despite the remarkable success of these novel therapies, the clinical benefit remains limited to a subset. As immunotherapy is expensive and could bring unnecessary toxicity there is a direct need to identify beneficial patients, but this remains difficult in clinical practice today. Radiomic biomarkers could address this, as, unlike…

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