Target Product Profile for a Machine Learning-Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study.

Background: Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation.

Preoperative Templating for Total Hip Arthroplasty: A Method for Calibrating Digital Radiographs Using Patient Demographics and Anthropometric Measurements.

Background Preoperative templating aids the surgeon in estimating implant size and placement. Calibration markers are used to set the correct magnification of digital images before templating. Improper marker placement or complete absence can lead to inaccuracy or an inability to calibrate images altogether.

Nottingham Hip Fracture Score: Does It Predict Mortality in Distal Femoral Fracture Patients?

Background Patients with distal femur fractures are associated with mortality rates comparable to neck of femur fractures. Identifying high-risk patients is crucial in terms of orthogeriatric input, pre-operative medical optimisation and risk stratification for anaesthetics. The Nottingham Hip Fracture Score (NHFS) is a validated predictor of 30-day mortality in neck of femur fracture patients.