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ABOUT MEABOUT ME

Alessandro

CicchettiLead Researcher and Data Scientist in Oncology
at Fondazione IRCCS Istituto Nazionale dei Tumori#Data Scientist#Clinical AIimgimg

Areas of Expertise

My work combines quantitative medical physics, machine learning, and clinical research methods to turn complex oncology data into reproducible evidence and practical decision-support tools.

Clinical Data Science

Predictive modeling, machine learning workflows, and statistical analysis for oncology datasets, with attention to reproducibility and clinical interpretability.

Radiotherapy Outcomes

Modeling treatment outcomes and toxicity patterns to support more personalized radiotherapy strategies and evidence-based clinical research.

Cardio-Oncology Research

Analysis of cardiac risk and treatment-related toxicity in cancer care, connecting imaging, clinical variables, and long-term patient outcomes.

Education

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MSc In Physics - (Exp. Particle Physics)

Sapienza University of Rome

2015
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PhD in Applied Physics for Medicine

University of Pavia

2020
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Specialization in Medical Physics

University of Milan

2023
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Experience

Lead Researcher and Principal Investigator

Fondazione IRCCS Istituto Nazionale dei Tumori
01/01/2023 Milan, Italy
Leading research activities focused on cardio-oncology in cancer treatment, with particular attention to radiotherapy-related cardiovascular toxicity and anti-VEGF therapies. Current work includes the development of a dedicated cardio-oncology research lab integrating four non-invasive research instruments, a CT-based software tool for cardiovascular risk assessment, and multidisciplinary studies involving three directly engaged researchers. The activity is built in close collaboration with clinicians in radiation oncology, cardiology, and pharmacology.

Medical Physics Trainee

San Raffaele Hospital
01/11/2020 Milan, Italy
Clinical training in medical physics, with exposure to radiotherapy workflows, treatment planning, imaging, quality assurance, and the clinical use of physics-based methods in patient care.

Data Science Consultant

Research Institutions and Companies
10/10/2019 Italy
Supporting research institutions and companies in statistical analyses aimed at scientific publication. Activities include study design support, data analysis, interpretation of clinical and biomedical datasets, preparation of reproducible analytical workflows, and methodological guidance for peer-reviewed research outputs.

Oncology Researcher

Fondazione IRCCS Istituto Nazionale dei Tumori
01/04/2015 Milan, Italy
Research activity within the Data Science Unit, focused on predictive modelling, quantitative imaging, radiotherapy outcomes, and clinical decision-support tools for oncology. Work included retrospective and prospective clinical studies, model development, validation strategies, and translational applications of data science in personalized medicine.
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Skills

Skills

Machine Learning
85%
Imaging Analysis
80%
Statistical Review
90%
Clinical Radiobiology
95%
Cardio-Oncology
75%
Digital Devices
80%

Selected Research Areas

Location Matters

A cardio-oncology research programme linking radiotherapy dose location, follow-up data, and personalised cardiovascular modelling.

    RAPID Solution

    A synthetic CT and deep learning study supporting patient selection for free breathing and deep inspiration breath hold radiotherapy.

      BIONCARD

      A cardio-oncology research line combining clinical data, imaging, and biological markers to support personalised risk assessment.

        Radiotherapy Studies

        Radiotherapy outcome studies focused on interpretable imaging, radiobiology, and clinically useful prediction.

          Digital Twins

          Personalised cardiovascular digital twins designed to explore mechanisms and support patient-specific decision making.

            Artificial Intelligence

            Machine learning and deep learning methods for imaging analysis, outcome prediction, and clinical decision support.

              Location Matters

              A cardio-oncology research programme linking radiotherapy dose location, follow-up data, and personalised cardiovascular modelling.

                RAPID Solution

                A synthetic CT and deep learning study supporting patient selection for free breathing and deep inspiration breath hold radiotherapy.

                  BIONCARD

                  A cardio-oncology research line combining clinical data, imaging, and biological markers to support personalised risk assessment.

                    Radiotherapy Studies

                    Radiotherapy outcome studies focused on interpretable imaging, radiobiology, and clinically useful prediction.

                      Digital Twins

                      Personalised cardiovascular digital twins designed to explore mechanisms and support patient-specific decision making.

                        Artificial Intelligence

                        Machine learning and deep learning methods for imaging analysis, outcome prediction, and clinical decision support.