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Deep learning derived mechanical biomarkers for cancer therapy prediction

CORDIS · observation · Publication date unknown

Deep learning derived mechanical biomarkers for cancer therapy prediction In the fight against cancer, it is well recognized that tumors are highly heterogeneous and they might differ considerably not only between tumors types but also among tumors of the same type or even for the same tumor during progression. As a result, the efficacy of standard cancer therapies varies, and while some patients respond to a particular treatment, other patients do not gain any benefit. Consequently, crucial in cancer therapy is the prediction of a patients response to treatment. Failure of standard therapies has led to the introduction of a new era of personalized, patient-specific treatments, which are based on the identification of biomarkers that characterize the state of a particular tumor. Many solid tumors (e.g., breast cancers and sarcomas) stiffen as they grow in a hosts normal tissue. Tumor sti

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recordType

award

status

CLOSED

region

EU

value

150000

unit

EUR