# AI-Enhanced Surgical Decision-Making in Orthopedics: From Preoperative Planning to Intraoperative Guidance and Real-Time Adaptation

## TL;DR

This paper reviews how AI is improving orthopedic surgery by enhancing preoperative planning, intraoperative guidance, and real-time decision-making.

## Contribution

The paper provides a comprehensive overview of AI applications in orthopedic surgery, emphasizing recent advancements and future directions.

## Key findings

- AI improves surgical precision and patient-specific customization through advanced imaging analysis and anatomical segmentation.
- Intraoperative AI systems enhance accuracy and reduce complications by integrating real-time image processing and robotic systems.
- AI applications in joint replacement, spine, and trauma surgery often outperform conventional methods in decision-making support.

## Abstract

Artificial intelligence (AI) is affecting the practice of orthopedic surgery, offering innovative solutions from preoperative planning to intraoperative guidance and real-time adaptation. This review highlights current advancements in AI-driven imaging analysis, anatomical segmentation, and implant selection, highlighting improvements in surgical precision, efficiency, and patient-specific customization. Intraoperatively, AI enables real-time image processing, integration with robotic systems, and adaptive feedback mechanisms that enhance accuracy, reduce complications, and personalize care. Clinical applications span joint replacement, spine, and trauma surgery, where AI supports diagnosis and offers support in decision-making, often surpassing conventional methods. Despite these promising developments, challenges remain regarding data quality, model generalizability, transparency, and ethical considerations. Future directions emphasize explainable AI, multimodal data integration, and closer synergy between AI, robotics, and digital health to advance personalized orthopedic care.