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Rationale And Objectives: Radiology is a rapidly evolving field that benefits from continuous innovation and research participation among trainees. Traditional methods for involving residents in research are often inefficient and limited, usually due to the absence of a standardized approach to identifying available research projects. A centralized online platform can enhance networking and offer equal opportunities for all residents.
Materials And Methods: Research Connect is an online platform built with PHP, SQL, and JavaScript. Features include project and collaboration listing as well as advertisement of project openings to medical/undergraduate students, residents, and fellows. The automated system maintains project data and sends notifications for new research opportunities when they meet user preference criteria. Both pre- and post-launch surveys were used to assess the platform's efficacy.
Results: Before the introduction of Research Connect, 69% of respondents used informal conversations as their primary method of discovering research opportunities. One year after its launch, Research Connect had 141 active users, comprising 63 residents and 41 faculty members, along with 85 projects encompassing various radiology subspecialties. The platform received a median satisfaction rating of 4 on a 1-5 scale, with 54% of users successfully locating projects of interest through the platform.
Conclusion: Research Connect addresses the need for a standardized method and centralized platform with active research projects and is designed for scalability. Feedback suggests it has increased the visibility and accessibility of radiology research, promoting greater trainee involvement and academic collaboration.
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http://dx.doi.org/10.1016/j.acra.2023.11.033 | DOI Listing |
BJGP Open
September 2025
Institute for Global Health, University College London, London, United Kingdom
Background: Over the past decade, remote (non-face-to-face) services are being increasingly used in primary care, including interactions through telephone and online platforms. These services bring potential benefits as well as potential barriers for patients. Older migrants are a population that could face intersectional barriers when accessing healthcare; it is important to understand the impact of remote services on them.
View Article and Find Full Text PDFInd Health
September 2025
Institute of Health Policy and Management, College of Public Health, National Taiwan University, Taiwan.
The rapid expansion of delivery labor platforms in China has driven many people to move from rural to urban areas. Previous studies indicated that platform-based delivery work can be demanding, subject to algorithmic control, and lacking employment protections. While migrant workers are more likely to be exposed to adverse psychosocial working conditions and more vulnerable due to limited social services, few studies have examined the role of migrant status in mental health and its associations with psychosocial working conditions among platform delivery workers.
View Article and Find Full Text PDFBr J Haematol
September 2025
Platform of Molecular Analysis for Mastocytosis and MCAD (CEREMAST), Department of Biological Hematology, Pitié-Salpêtrière Hospital, AP-HP, Paris Sorbonne University, Paris, France.
Mastocytosis is categorized into cutaneous mastocytosis (CM), mast cell sarcoma and systemic mastocytosis (SM). Within SM, indolent SM (ISM) is the more frequent subtype. Adult patients with CM but without an extracutaneous biopsy are classified as having mastocytosis in the skin (MIS), a provisional diagnosis.
View Article and Find Full Text PDFBMJ Open
September 2025
Pharmacy Department, St John of God University Hospital, Dublin, Ireland.
Objectives: To address the lack of accurate and accessible mental health medicines-information resources for children, young people and their parents/guardians using design thinking to co-design free-to-use, video resources tailored to this audience.
Design: A multiphase qualitative case study using the Double Diamond model of Design Thinking: Discover, Define, Develop and Deliver. This included iterative prototyping, thematic analysis and public and patient involvement throughout.
Radiother Oncol
September 2025
Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China; School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China. Electronic address:
Background And Purpose: Determining the appropriate sample size for developing robust radiomics-based binary outcome prediction models and identifying the maximum number of predictors safely allowable within a fixed dataset size remain critical yet challenging tasks. This study aims to propose and demonstrate a structured method for addressing these issues, enhancing methodological rigor and practicality in radiomics research.
Materials And Methods: We introduce a comprehensive sample size calculation framework for binary outcome prediction models in radiomic studies.