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Artificial intelligence for Health

Topic Leader: Andrea Barucci

Precision medicine is a medical model that proposes the customization of healthcare, with medical decisions and treatments being tailored to the individual patient. In this model, diagnostic tools as molecular and genetic analysis, imaging, and analytics are employed for selecting appropriate and optimal therapies.

Artificial Intelligence (AI) in Healthcare and Well-Being is a very broad field of research, ranging from drug discovery and imaging to wearable sensors. Probably the huge impact of AI in medicine is due to its intrinsic ability to model and discover complex pattern in high-dimensional data, which is very suitable for the precision medicine approach.

Radiomics essentially means the extraction of a high number of quantitative features (descriptors of an image) from medical images, aiming to develop diagnostic/predictive/prognostic model in the framework of precision medicine (supporting personalized clinical decisions and improving individualized treatment selection). Radiomics allows to move from «qualitative» to «quantitative» and data-driven information.

Artificial Intelligence applications for Imaging Biobank

We are involved in different projects aiming to build imaging biobanks (the first for Tuscany region) and platforms, to boost 4P precision medicine in oncology by advancing translational research based on quantitative imaging and multi-omics analyses, towards a better understanding of cancer biology, cancer care, and, more generally, cancer risk.

For more info please contact Andrea Barucci

Main references:

Radiomics in Alzheimer disease

In this activity we aim to use the “radiomic approach” to MRI-images of Alzheimer’s patients, in a multi-disciplinary approach integrating other omics techniques. Collected data will be analyzed using machine learning and deep learning techniques.

For more info please contact Andrea Barucci

Main references:

  • Barucci A, D’Andrea C, Farnesi E, Banchelli M, Amicucci C, de Angelis M, Hwang B, Matteini P. Label-free SERS detection of proteins based on machine learning classification of chemo-structural determinants. Analyst. 2020 Nov 19. doi: 10.1039/d0an02137g.

Radiomics in COVID19-disease

In this activity we aim to use statistics and artificial intelligence techniques to clinical and omics data, as well as clinical images, of patients with COVID19, in a multi-disciplinary approach. Collected data will be analyzed to understand the best approach for diagnosis/therapy of the disease in the framework of precision medicine.

For more info please contact Andrea Barucci

Current members:

  • Andrea Barucci (topic leader)
  • Paolo Matteini
  • Fulvio Ratto