- Implementation of advanced classification and predictive models based on radiomics features and machine learning strategies as decision support tools in computed aided surgery and radiotherapy
- On-going development of deep learning methods for tumor classification and segmentation, along with improvement of predictive models
- Implementation of Explainable AI (XAI) models to provide predictive tools for informed decision-making in medical imaging in oncology
- Implementation of structured repositories to support radiomics and AI studies.
A research collaboration on this topic is ongoing with the Radiotherapy and Radiology Unit of the Istituto Europeo di Oncologia, also in the framework of the AIRC project “CT screening for lung cancer: investigating early diagnosis with Artificial Intelligence and Radiomics”.
Activities on XAI models are in collaboration with Università degli Studi di Milano Bicocca (Milano, Italy) and CERN (Geneve, Switzerland).
