PhD Alberto Traverso – “Quantitative imaging in radiation oncology”

Dissertation title: “Quantitative imaging in radiation oncology”

Summary

“Artificially intelligent” eyes, built on machine and deep learning technologies, can empower our capability of analyzing patients’ images. By revealing information invisible at our eyes, we can build decision aids that help our clinicians to provide more effective treatment, while reducing side effects. The power of these decision aids is to be based on patient tumor biologically unique properties, referred to as biomarkers.

To fully translate this technology into the clinic we need to overcome barriers related to the reliability of image-derived biomarkers, trustiness in AI algorithms and privacy-related issues that hamper the validation of the biomarkers.

Alberto Traverso: “In my thesis I developed methodologies to solve the presented issues, defining a road map for the responsible usage of quantitative imaging into the clinic as decision support system for better patient care.

Finally, my research tackles some of the problems related to the introduction of AI to improve our ability to make better-informed decisions. When it comes to be supported by AI in our decisions, we are more reluctant to accept this shift in paradigm. I have proposed methods that can support more transparent and robust developments of image-derived biomarkers and shown how cautions are required when using AI. My research is proposing the paradigm to re-shift human-centricity when using AI. This will have a strong cultural impact, and, in my opinion, it will boost the acceptance of AI, not only for clinicians, but also for patients, academia and society.”