Big data and artificial intelligence in Orthopaedics: Trends and future directions

Area of Science:

• Orthopaedic Surgery
• Medical Informatics
• Data Science

Background:

• Traditional orthopaedic data relies on manual records.
• Emerging automated data collection and population registries generate vast "big data" datasets.
• Existing tools struggle to process these large, complex datasets.

Purpose of the Study:

• To review the emerging opportunities and challenges of big data and AI in orthopaedic surgery.
• To explore necessary guardrails for safe and sustainable integration of these technologies.
• To highlight the transformative potential of AI and big data in clinical applications and research.

Main Methods:

• Narrative review of current literature on big data and AI in orthopaedic surgery.
• Analysis of the impact of big data on data processing capabilities.
• Exploration of AI's role in meaningfully processing big data.

Main Results:

• Big data and AI are poised to revolutionize orthopaedic surgery.
• Significant advancements in research and clinical applications are enabled by these technologies.
• The integration of big data and AI presents both opportunities and challenges.

Conclusions:

• The fusion of big data and AI offers unprecedented potential for orthopaedic surgery.
• Careful consideration of safety protocols and ethical guidelines is crucial for responsible implementation.
• Sustainable progress requires a strategic approach to managing and utilizing these powerful tools.