The number of convolutional neural networks (CNN) available for fracture detection and classification is rapidly increasing. External validation of a CNN on a temporally separate (separated by time) or geographically separate (separated by location) dataset is crucial to assess generalizability of the CNN before application to clinical practice in other institutions. We aimed to answer the following questions: are current CNNs for fracture recognition externally valid?; which methods are applied for external validation (EV)?; and, what are reported performances of the EV sets compared to the internal validation (IV) sets of these CNNs? The PubMed and Embase databases were systematically searched from January 2010 to October 2020 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The type of EV, characteristics of the external dataset, and diagnostic performance characteristics on the IV and EV datasets were collected and compared. Quality assessment was conducted using a seven-item checklist based on a modified Methodologic Index for NOn-Randomized Studies instrument (MINORS).Aims
Methods
The Intraosseous Transcutaneous Amputation Prosthesis (ITAP)
may improve quality of life for amputees by avoiding soft-tissue
complications associated with socket prostheses and by improving
sensory feedback and function. It relies on the formation of a seal
between the soft tissues and the implant and currently has a flange
with drilled holes to promote dermal attachment. Despite this, infection
remains a significant risk. This study explored alternative strategies
to enhance soft-tissue integration. The effect of ITAP pins with a fully porous titanium alloy flange
with interconnected pores on soft-tissue integration was investigated.
The flanges were coated with fibronectin-functionalised hydroxyapatite
and silver coatings, which have been shown to have an antibacterial
effect, while also promoting viable fibroblast growth Aims
Materials and Methods
