Research
Our research program encompasses ongoing clinical trials, studies in preparation, and published findings across AI evaluation in trauma and emergency medicine.
AI Fracture Trial
A multicenter randomized controlled trial involving 3,000 patients to evaluate diagnostic accuracy and treatment efficiency of AI-assisted fracture detection in real clinical workflows. This comprehensive study addresses cost-efficiency evaluation in emergency medicine settings.
AI in Bone Lesion Assessment and Diagnostic Decision-Making
Comprehensive evaluation of artificial intelligence applications in bone pathology detection and diagnostic workflow integration. This study examines AI performance across various bone lesion types and assesses clinical decision-making impact.
AI in Joint Effusion Detection in Acute MSK Imaging
Investigation of AI-assisted detection and quantification of joint effusions in emergency and acute care radiology. This study evaluates diagnostic accuracy, workflow integration, and clinical decision-making impact in musculoskeletal emergency imaging.
Predictive Modeling for Acute Trauma Care
Development and validation of predictive models for acute trauma care optimization. Focus on AI-driven decision support systems for emergency trauma management, integrating clinical workflows with advanced predictive analytics.
Failure Analysis of AI in Skeletal Radiography
Systematic analysis of AI system failures in skeletal imaging interpretation. This study identifies failure patterns, clinical risk factors, and mitigation strategies for AI-assisted radiological diagnosis in musculoskeletal medicine.
FRISK Trial — AI-Supported Injury Assessment
Clinical trial evaluating AI-assisted injury assessment and diagnostic workflows in emergency and trauma settings. This study examines the integration of artificial intelligence tools into clinical practice.
NLP Evaluation of Self-Injury Trends
Advanced natural language processing analysis of clinical documentation to identify patterns, trends, and risk factors in self-injury cases. This longitudinal study provides insights into changing injury patterns and healthcare utilization.
Physician Acceptance of AI Solutions in Emergency Departments
Cross-disciplinary analysis of physician acceptance of AI in fracture detection using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Surveyed across orthopaedic surgery, pediatric surgery, and radiology departments.
NLP Analysis — Value-Based Medicine
Two complementary studies re-evaluating routine imaging after central venous catheter procedures. Combining NLP-driven analysis of pneumothorax incidence with cost-effectiveness modelling to support evidence-based imaging protocols.