Sports are characterized by unique rules, environments, and tasks, but also share fundamental similarities with each other sport. Such between-sports parallels can be vital for optimizing talent transfer processes. This study aimed to explore similarities between sports to provide an objective basis for clustering sports into families by means of machine learning.
View Article and Find Full Text PDFBackground: Previously published research describes short-term outcomes after proximal interphalangeal (PIP) joint arthroplasty, however, long-term outcomes are scarce. Therefore, we evaluated patient-reported outcomes and complications after a follow-up of at least five years following PIP joint arthroplasty.
Methods: We used prospectively gathered data from patients undergoing PIP joint arthroplasty with silicone or surface replacement implants.
Background: Color match of a reconstructed breast with the surrounding area is of importance for the overall aesthetic result. The objective of the authors' study was to quantify the degree of color match achieved with different autologous breast reconstructions and to analyze the changes in color over time by analyzing digital photographs.
Methods: A total of 193 patients who underwent a delayed autologous breast reconstruction (deep inferior epigastric perforator [DIEP], profunda artery perforator [PAP], lumbar artery perforator [LAP], latissimus dorsi [LD]) were included.
Well-designed talent programmes in sports with a focus on talent identification, orientation, development, and transfer support the engagement of young individuals and the pursuit of elite performance. To facilitate these processes, an analysis of task, environmental and individual characteristics per sport is much needed. The aims of this study were to 1) analyse whether unique profiles per sport could be established by generic characteristics and 2) to discuss similarities and differences for the potential application in talent development and transfer.
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