Harmonized and interoperable data management is a core requirement for federated infrastructures in clinical research. Institutions participating in such infrastructures often have to invest large degrees of time and resources in implementing necessary data integration processes to convert their local data to the required target structure. If the data is already available in an alternative shared data structure, the transformation from source to the desired target structure can be implemented once and then be distributed to all participants to reduce effort and harmonize results. The HL7® FHIR® standard is used as a basis for the shared data model of several medical consortia like DKTK and GBA. It is based on so-called resources which can be represented in XML. Oncological data in German university hospitals is commonly available in the ADT/GEKID format. From this common basis we conceptualized and implemented a transformation which accepts ADT/GEKID XML files and returns FHIR resources. We identified several problems with using the general ADT/GEKID structure in federated research infrastructures, as well as some possible pitfalls relating to the FHIR need for resource ids and focus on semantic coding which differs from the approach in the ADT/GEKID standard. To facilitate participation in federated infrastructures, we propose the ADT2FHIR transformation tool for partners with oncological data in the ADT/GEKID format.
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J Am Board Fam Med
January 2025
From the Department of Family Medicine and Community Health, Rutgers Health, 303 George Street, Matrix Plaza 1, Room 614, New Brunswick, NJ (AFT, JMF, MEJ, MP, MFC, EJ, SVH); New Jersey Alliance for Clinical and Translational Science, New Brunswick, NJ (AFT, DH, MEJ, SVH); Office of University-Community Partnerships, Rutgers University, Newark, NJ (DH); Department of Pediatrics, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ (MEJ); Rutgers Robert Wood Johnson Medical School, Rutgers Institute for Translational Medicine and Science, New Brunswick, NJ, USA (SVH).
Many academic departments and programs struggle with the challenge of how to begin a meaningful research program. A useful place to start is with the work they already are doing in communities. Using work in practices and other clinical venues as a springboard can build helpful relationships that can catalyze research and build infrastructure that matters to family medicine clinicians, researchers, and the communities they serve.
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Wildlife Observatory of Australia (WildObs), Queensland Cyber Infrastructure Foundation (QCIF), Brisbane, Queensland, 4072, Australia.
Camera traps are widely used in wildlife research and monitoring, so it is imperative to understand their strengths, limitations, and potential for increasing impact. We investigated a decade of use of wildlife cameras (2012-2022) with a case study on Australian terrestrial vertebrates using a multifaceted approach. We (i) synthesised information from a literature review; (ii) conducted an online questionnaire of 132 professionals; (iii) hosted an in-person workshop of 28 leading experts representing academia, non-governmental organisations (NGOs), and government; and (iv) mapped camera trap usage based on all sources.
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January 2025
Department Sanitary and Environmental Engineering, Rio de Janeiro State University-UERJ, Rio de Janeiro, CEP, Brazil.
Determining environmental risk levels posed to different urban lagoon can provide an important overview regarding the relative severity of the environmental degradation of these ecosystems, increasing the risks visibility, which can be used as an important decision-making tool to prioritize investments. Jacarepaguá Lagoon (JPAL) is part of a coastal lagoon system comprising four interconnected lagoons in Rio de Janeiro city, Southeastern Brazil. Real estate speculation and insufficient sanitation infrastructure resulted in untreated sewage discharge into this ecologically sensitive lagoon system.
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January 2025
Hochschule für Technik und Wirtschaft Berlin (HTW Berlin), Berlin, Germany.
Road unevenness significantly impacts the safety and comfort of traffic participants, especially vulnerable groups such as cyclists and wheelchair users. To train models for comprehensive road surface assessments, we introduce StreetSurfaceVis, a novel dataset comprising 9,122 street-level images mostly from Germany collected from a crowdsourcing platform and manually annotated by road surface type and quality. By crafting a heterogeneous dataset, we aim to enable robust models that maintain high accuracy across diverse image sources.
View Article and Find Full Text PDFACS Sens
January 2025
Sensor Engineering Department, Faculty of Science and Engineering, Maastricht University, P.O. Box 616, 6200 MDMaastricht, The Netherlands.
Malaria is a major public healthcare concern worldwide, representing a leading cause of death in specific regions. The gold standard for diagnosis is microscopic analysis, but this requires a laboratory setting, trained staff, and infrastructure and is therefore typically slow and dependent on the experience of the technician. This study introduces, for the first time, a biomimetic sensing platform for the direct detection of the disease.
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