AI for Life Sciences

Our mission is focused on the development, evaluation and dissemination of new Artificial Intelligence (AI) methods in Life Sciences. Our interdisciplinary AI research includes methodological advances in the foundations of AI along with the development of transformative medical AI applications to improve the understanding of healthy and pathological processes and advance patient health. Patient-specific AI models are designed by exploring both conventional machine learning and modern deep learning strategies. 

The main fields of application are: 

  • AI in Neurology: prediction of cognitive decline and dementia 
  • AI for healthy ageing: prediction of functional decline, falls, and adverse events 
  • AI for predictive, personalized, preventive, and participatory (P4) medicine:
    • AI to predict lung cancer
    • AI for the design of digital risk screening tools and digital biomarkers discovery 
  • AI for augmented reality in robot-assisted surgery 
  • AI methods inspired by Neuroscience 
  • AI in movement analysis: physical activity and motor impairment classification 
  • AI for the analysis and decoding of brain signals 

ERC Fields 

  • LS5_10 Neuroimaging and computational neuroscience 
  • LS7_1 Medical engineering and technology 
  • LS7_2 Diagnostic tools (e.g. genetic, imaging) 
  • PE6_11 Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video 

Scientific coordinator: Prof. Stefano Diciotti

Faculty

Lorenzo Chiari

Full Professor

Cristiana Corsi

Associate Professor

Cristiano Cuppini

Senior assistant professor (fixed-term)

Stefano Diciotti

Associate Professor

Elisa Magosso

Associate Professor

Sabato Mellone

Junior assistant professor (fixed-term)

Mauro Ursino

Full Professor

Other people

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