The treatment of bone defects and orthopedic infections as well as artificial intelligence (AI) integration into medical practice present innovative but complex challenges. Regarding bone loss, current approaches such as decellularized allografts and adipose-derived stem cells improve biocompatibility and osteogenic potential. However, challenges like vascularization and costs remain unresolved.
Orthopedic infections require early diagnosis and multidisciplinary management. Specific classifications, such as Oxford’s, help personalize treatments. Despite the complexity of severe cases, strategies combining debridement, antibiotics, and bone reconstruction yield promising results. Emerging therapies target biofilms with enzymatic cocktails and localized antibiotics, offering potential clinical applications.
AI is also transforming orthopedics through neural networks and explainability-focused models. These technologies improve diagnosis and surgical planning, but their adoption requires greater transparency in decision-making processes. Techniques like "poly-CAM" increase clinicians’ trust by providing reliable visual tools for interpreting data. These advances pave the way for predictive and personalized medicine, reshaping clinical practices.
Keywords
Regenerative medicine, bone substance loss, allografts, bioengineering, stem cells, artificial intelligence (AI), convolutional neural networks (CNNs), explainability, osteoarticular infections, diagnosis, prosthetic joint infections, multidisciplinary approach