Machine Learning-Assisted Ag-TiO₂ SERS Platform for Intraoperative Osteomyelitis Diagnosis

Key Points

• To develop and assess a machine learning-assisted platform for diagnosing intraoperative osteomyelitis.
• Developed an Ag-TiO₂ SERS platform for bio-sensing.
• Employed machine learning algorithms to analyze diagnostic data.
• Compared the sensitivity and specificity to traditional diagnostic methods.
• Achieved significantly higher sensitivity compared to bacterial culture methods.
• Demonstrated improved specificity in differentiating osteomyelitis.
• Utilized real-time analysis for faster diagnostic outcomes.