Optimisation of personalised treatments for femoral fractures using digital twins and machine learning
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PID2022-140539OB-I00
The objective is the improvement and/or adaptation of current surgical techniques for the treatment of femur fractures, in the direction of analysing and comparing the use of intramedullary nails and lateral plates depending on the type of fracture and patient. Quantifying the stabilising properties in each case and the improvements in terms of the most appropriate locking configurations for each case. The results obtained are synthesised in a system based on artificial intelligence to support decision-making by medical specialists in real time.