26 research outputs found
Concussions in Sledding Sports and the Unrecognized “Sled Head”: A Systematic Review
Background: Sport-related concussion is a significant public health concern. Little research has been conducted on sport-related concussion and injury prevention strategies in competitive sledding sports like bobsleigh, luge, and skeleton. Athletes have identified “sled head” as a key concern due to its symptom burden.Purpose: To summarize our knowledge of the prevalence of concussion and related symptoms in sledding sports; to utilize Haddon's Matrix to inform and define strategies for injury prevention.Methods: An independent information specialist conducted a search for the known literature on injuries in non-recreational sledding sports, and specifically for concussion via OVID Medline, CINAHL, the Cochrane Database, EMBASE, PsycInfo, PubMed, Scopus, and the Web of Sciences from 1946 to December 2017. After iterative searches of reference sections, a total of 844 articles were assessed for inclusion.Results: Nine articles were included for review. Concussions are a common occurrence in elite sledding sport athletes, affecting 13-18% of all sledding athletes. Significant variance exists between events, indicating a potential effect of the ice track in injury risk. The condition known as “sled head” is discussed and identified as a key point of further investigation. A number of potential injury prevention strategies are discussed.Interpretation: Head injuries and concussions are an important injury for elite sledding sports and a number of avenues exist for prevention. More work is required to delineate the mechanisms, characteristics, natural history and management of “sled head.
Issues and Challenges in Applications of Artificial Intelligence to Nuclear Medicine -- The Bethesda Report (AI Summit 2022)
The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI
AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought
together various community members and stakeholders from academia, healthcare,
industry, patient representatives, and government (NIH, FDA), and considered
various key themes to envision and facilitate a bright future for routine,
trustworthy use of AI in nuclear medicine. In what follows, essential issues,
challenges, controversies and findings emphasized in the meeting are
summarized
Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines
The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77–94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines
Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (Nature Medicine, (2022), 28, 5, (924-933), 10.1038/s41591-022-01772-9)
In the version of this article initially published, a list of the DECIDE-AI expert group members and their affiliations was omitted and has now been included in the HTML and PDF versions of the article. *A list of authors and their affiliations appears online