Machine Learning techniques application to predict the quality of life degree in breast cancer patients.

Breast cancer is among the leading causes of mortality in women of all ages worldwide. Prevention and timely diagnosis can make the difference between life and death for most patients, and it is for this reason that today there is a great deal of focus on raising public awareness about the possibility of using the various techniques of preventive screening available today. In cases where surgery is necessary, beyond the purely medical aspects, it is important to take into account also the psychological aspects, which are sometimes underestimated with negative consequences for the patient. However, it is very difficult to determine a priori what the final outcome of the intervention will be, especially with regard to the level of personal satisfaction of patients. The aim of this work is to identify a possible correlation between the commonly used measurements of breast morphology, necessary for the assessment of any surgical procedure, and the personal satisfaction level of the patients, based on the results of anonymous questionnaires, through the use of machine learning techniques.