Medical image analysis for virtual biopsy and personalized prognostic profiling in clinical pathway - Lara Cavinato
15 October 2020 - 15 October 2020
Clinical decision support systems, or CDSSs, represent a paradigm shift in healthcare today as they are expected to aid clinicians in their complex decision-making processes, encompassing data of different type and source. In oncology, most of the information used for devising optimal and personalized prognostic profiling is biological, which is time- and resource-demanding to retrive, thus unfeasible to enter a CDSS workflow. Here comes the hypothesis that imaging-derived information, namely radiomics, can be a surrogate for biological characterization of tissues, performing the so-called "virtual biopsy" and informing the entire treatment planning. Given this rationale, some example of application as well as open issues and future directions will be further discussed.

The speaker

Lara Cavinato is a PhD student in Data Analytics and Decision Science at Politecnico di Milano; she spent visiting periods at the Sinha Lab (MIT) and at the Humanitas Research Hospital.