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Transformers for Neuroimage Segmentation: Scoping Review.
J Med Internet Res
January 2025
Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFImpact of Online Interactive Decision Tools on Women's Decision-Making Regarding Breast Cancer Screening: Systematic Review and Meta-Analysis.
J Med Internet Res
January 2025
Cancer Screening, American Cancer Society, Atlanta, GA, United States.
Background: The online nature of decision aids (DAs) and related e-tools supporting women's decision-making regarding breast cancer screening (BCS) through mammography may facilitate broader access, making them a valuable addition to BCS programs.
Objective: This systematic review and meta-analysis aims to evaluate the scientific evidence on the impacts of these e-tools and to provide a comprehensive assessment of the factors associated with their increased utility and efficacy.
Methods: We followed the 2020 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted a search of MEDLINE, PsycINFO, Embase, CINAHL, and Web of Science databases from August 2010 to April 2023.
Effectiveness of Different Intervention Modes in Lifestyle Intervention for the Prevention of Type 2 Diabetes and the Reversion to Normoglycemia in Adults With Prediabetes: Systematic Review and Meta-Analysis of Randomized Controlled Trials.
J Med Internet Res
January 2025
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Background: Lifestyle interventions have been acknowledged as effective strategies for preventing type 2 diabetes mellitus (T2DM). However, the accessibility of conventional face-to-face interventions is often limited. Digital health intervention has been suggested as a potential solution to overcome the limitation.
View Article and Find Full Text PDFHelping authors produce FAIR taxonomic data: evaluation of an author-driven phenotype data production prototype.
Database (Oxford)
January 2025
Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON CA K1A 0C6, Canada.
It is well-known that the use of vocabulary in phenotype treatments is often inconsistent. An earlier survey of biologists who create or use phenotypic characters revealed that this lack of standardization leads to ambiguities, frustrating both the consumers and producers of phenotypic data. Such ambiguities are challenging for biologists, and more so for Artificial Intelligence, to resolve.
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