Age-related bone fractures are a major health concern, resulting worldwide in high economic and psycho-social burden, morbidity and increasing mortality. With aging and in presence of bone pathologies, human bone becomes more brittle and prone to damage.
A clinical hypothesis considers Covid-19 virus as an additional contributing factor in bone deterioration. At the macro-scale, the identification of fragility is assured by the clinical practice: common clinical tools, however, are able to predict only 70% of fractures. For this reason, a deep investigation of bone micro-architecture would be a hint for the comprehension of damage mechanisms, improving the reliability of fracture risk indicators and performing more accurate diagnosis of bone pathologies. This knowledge level goes beyond the current state of the art and here GAP comes into play, providing multi-disciplinary and versatile training strategies for comprehension, detection and patient-specific treatments of bone fractures. The main aim of GAP is to educate young and talented scientists towards a combined high-level experimental and numerical approach for the early-stage accurate, precise detection and mini-invasive treatments of bone fractures, shedding some light on bone micro-scale alterations due to pathologies. The inter-disciplinary findings, that exploit multi-scale imaging facilities and advanced artificial intelligent-based strategies, will be a crucial aspect in the training of skilled researchers.