Thursday, 18th of March 2021, 12:00 – 1:00

Machine learning in decoding and driving clinical cancer care

Please use this link & sign in with your real name

Dalibor Hrg
Researcher at DBIS, University of Innsbruck & CCB Medical University of Innsbruck


Artificial intelligence (AI) and machine learning (ML) play a role in many deployed decision systems today. Explaining, in a human-understandable way, the relationship of input and output of ML models is essential to the trustworthiness of such systems in high impact areas such as finance or medicine. In radiology and oncology as branches of medicine and clinical practice, as well as in pharma and IT companies, AI/ML is increasingly used for predictive modeling with genomic and/or diverse imaging data (radiomics) in order to understand patient survival, cancer treatment responses, or to stratify patients for clinical benefit. Chemotherapy is a major treatment modality utilized by oncologists in clinics, next to operation, radiotherapy or in combination with immunotherapies. Nevertheless, across all cancer types, patient responses to drugs are low, and systematically not yet understood - an open problem in "Deep Medicine". Advances in interpretable machine learning have not yet been fully utilized, opening opportunity for engineering new curative drug combinations and driving curative cancer care. 


Nach oben scrollen