🔰 JOCR Article of the Day: Machine Learning-Assisted Pre-operative Planning for Joint Replacement Surgery: Accuracy, Validation, and Post-operative Critical Analysis – A Retrospective Case Series — a study showing how AI can help plan hip replacements more accurately and safely.
🔶 Read Free Full Text: https://jocr.co.in/wp/2025/12/machine-learning-assisted-pre-operative-planning-for-joint-replacement-surgery-accuracy-validation-and-post-operative-critical-analysis-a-retrospective-case-series/
✍ Authored by: Dr. Vinit Kumar Singh, Dr. Himanshu Bajpai, Dr. Prashant Kumar Sharma, Dr. Gaurav Gupta
🧠 Key Insight: This retrospective case series evaluated a machine learning (ML)-assisted pre-operative templating system for total hip arthroplasty (THA) in nine consecutive patients. The ML tool predicted implant details — like stem type and size, cup size, and material — with an overall accuracy of 85.7 % when compared with actual intraoperative selections. Component-specific accuracy was highest for stem type and material selection and lowest for head sizing. The system also correctly predicted a needed implant conversion in one case. All nine patients had successful surgeries with no complications at mid-term follow-up, supporting the feasibility and clinical safety of ML-assisted planning and highlighting the need for larger studies.
✅ JOCR is now accepting Original Articles & Case Series: https://www.jocr.co.in/wp/submit-article/
🔆 JOCR Indexed with PubMed & DOAJ.