Track: Artificial Intelligence and Data Driven Orthopedics

Artificial intelligence and data-driven technologies are increasingly discussed as transformative forces in orthopedic surgery, closely connected to advances explored in 3D printing and digital technology and robotic and computer-assisted orthopedic surgery. This session offers a grounded, evidence-based examination of current and emerging AI applications across the field.

Key Topics and Highlights:

Predictive Models for Surgical Outcomes: Machine learning models are being developed to predict complications and functional recovery. This subtopic reviews current validation data and generalizability challenges.

AI-Assisted Imaging and Diagnostic Support: Automated image analysis supports preoperative planning and diagnosis of fractures or implant loosening. This subtopic examines current accuracy and clinical integration barriers.

Wearable Sensors and Remote Monitoring: Continuous data on patient mobility and gait may inform more personalized rehabilitation, connecting to themes in orthopedic rehabilitation and physiotherapy. This subtopic explores current evidence.

Data Quality and Algorithmic Bias: AI tools are only as reliable as the data they are trained on. This subtopic addresses the importance of representative datasets in clinical AI development.

Ethical Considerations in AI-Assisted Decision-Making: Maintaining surgeon judgment alongside data-driven tools remains essential. This subtopic discusses privacy, bias, and appropriate clinical integration of AI.

If your research advances AI or data-driven approaches in orthopedics, we welcome you to submit an abstract and contribute to a rapidly evolving, evidence-focused area of the field.

International Conference on Arthroplasty and Orthopedic Research

Track: Artificial Intelligence and Data Driven Orthopedics

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