aceTransitioning to expert-in-the-loop AI explainability in orthopaedic practice: Opportunities, challenges, and outlook
Artificial intelligence (AI) is demonstrating very successful applications in orthopaedics, ranging from medical imaging interpretation and risk prediction to surgical planning and post operative monitoring. Yet, many AI systems remain difficult to trust in real-world clinical workflows because they are often optimized for standalone accuracy rather than clinically useable transparency, human AI teamwork, and safe escalation when the AI models are uncertain. Experts-in-the-loop explainability re frames explainab…
Many orthopaedic AI systems are hard to trust in real clinical workflows because they prioritize standalone accuracy over usable transparency, human-AI teamwork and safe escalation when uncertain.
The source is a perspective that outlines opportunities, challenges and an outlook, and it names unresolved issues such as unreliable saliency maps and unclear medico-legal responsibility, without reporting measured outcomes.
Evidence
- Peer-reviewedJournal of Clinical Orthopaedics and Trauma2026-09-21
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Truvace Impact Record TRV-2026-1793, v1: “Transitioning to expert-in-the-loop AI explainability in orthopaedic practice: Opportunities, challenges, and outlook.” Truvace, 2026-10-18. /record/TRV-2026-1793 (accessed at citation time). sha256 d1efebb0e5df9ec3…
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