Digital twins: pioneering personalized precision in modern surgery

Surgical planning and execution have traditionally relied on generalized approaches, often overlooking patient-specific anatomical and physiological variations, leading to increased risks and variable outcomes. Digital twins, virtual replicas of patients that integrate real-time data and predictive modeling, are emerging as a transformative innovation in surgery. These models enable personalized simulations for preoperative planning, intraoperative guidance, and postoperative monitoring, enhancing precision and reducing complications. However, barriers such as data privacy, computational demands, and regulatory hurdles limit their integration. Future advancements should emphasize interdisciplinary collaboration, standardized protocols, and clinical trials to realize their full potential in democratizing precision surgery.