Current and emerging therapies for knee osteoarthritis: From conventional approaches to machine learning and stem...

Osteoarthritis is characterized by cartilage degradation and joint distortion. The most prevalent version of osteoarthritis, knee osteoarthritis (KOA), affects millions, acting as a leading cause of disability. With the average life expectancy continuing to grow, the global burden of KOA is expected to increase. KOA involves chronic pain that limits function and adversely impacts patients' quality of life. Long-term management is costly and burdensome, often requiring continuous treatment that only delays disease progression unless patients receive a total knee arthroplasty. Recently, traditional treatment modalities for KOA have been augmented by advancements in machine learning (ML), which enable automated disease grading, predictive modeling for early diagnosis, and personalized treatment strategies, alongside growing interest in stem cell-based therapies. With the goal of developing less invasive treatments that slow or reverse KOA progression, investigation into these novel therapies have increased. Stem cell-based therapies offer the potential to modulate inflammation, reduce pain, and preserve cartilage integrity, addressing key limitations of existing treatments. Mesenchymal stem cells have shown promising preclinical and clinical results, demonstrating improvements in pain, function, and cartilage-related outcomes through immunomodulatory and paracrine mechanisms. This narrative review synthesizes current evidence on conventional and emerging therapies for KOA, with a dual focus on ML-driven clinical applications and stem cell-based regenerative strategies, and discusses their potential roles in improving diagnosis, treatment selection, and patient outcomes. While further research is needed to understand the full potential of stem cells for treating KOA, these promising findings make it a useful topic for current and future clinical applications.