Using artificial intelligence to predict choledocholithiasis: can machine learning models abate the use of MRCP in patients with biliary dysfunction?

Background: Prompt diagnosis of choledocholithiasis is crucial for reducing disease severity, preventing complications and minimizing length of stay. Magnetic resonance cholangiopancreatography (MRCP) is commonly used to evaluate patients with suspected choledocholithiasis but is expensive and may delay definitive intervention. To optimize patient care and resource utilization, we have developed five machine learning models that predict a patients' risk of choledocholithiasis based on clinical presentation and pre-MRCP investigation results.

3D-printed Titanium Prosthetic Reconstruction of the C2 Vertebra: Techniques and Outcomes of Three Consecutive Cases.

Study Design: Three patients were treated at our center with patient-specific three-dimensional (3D)-printed titanium prostheses for the reconstruction of structurally compromised C2 vertebrae.

Objective: To describe our surgical and device design approach to these clinical scenarios and evaluate their outcomes.

Summary Of Background Data: There are a limited but increasing number of case reports and series describing the use of 3D-printed prostheses for high cervical surgery.