DIETI Contact person / Partner: Nicola Pasquino
Abstract
Understanding when a patient with bladder cancer is in a real progression of disease requires a great deal of interpretation of a huge amount of data that often may not be analyzed effectively by the oncologist when a decision must be taken. The aim of the research is to develop an appropriate classification of cancer that indicates, through machine learning techniques and statistical analysis of patients’ clinical variables, the status of the bladder cancer, how it is progressing and if a change of therapy is needed. The research will be in cooperation with Clinical Research Technology S.r.l. (IT), European Institute of Oncology (IT) and Klinik Sankt Moritz (CH).
Objective
The aim is to help the oncologist to better understand when a change of therapy is needed through machine learning methodologies and statistical analysis of clinical variables such as the patient's medical condition, the aggressiveness of the cancer, the effectiveness of the treatments.
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Can be assigned to one doctoral student of cycle XXXVI