13 research outputs found

    The Function Biomedical Informatics Research Network Data Repository

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    The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical datasets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 dataset consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 Tesla scanners. The FBIRN Phase 2 and Phase 3 datasets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN’s multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data

    “Failing Up” on Social Media—Finding Opportunities in Moments of #Fail

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    This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Social media (SoMe) has been utilized for many years for medical education but has recently grown because of the increase in online learning during the coronavirus disease 2019 (COVID-19) pandemic. Several SoMe platforms are commonly used for online medical education (eg, Twitter [Twitter Inc, San Francisco, California], Instagram [Facebook, Inc, Menlo Park, California], Facebook [Facebook, Inc, Menlo Park, California]) [1, 2, 3]. Twitter has become popular among radiologists for medical education with obstacles occurring along the way. This article represents a collection of experiences from three neuroradiologists who use Twitter to disseminate case-based radiology education as part of institutionally approved curricula. In this article, we share advice for those interested in utilizing SoMe for medical education purposes, including experiences in which obstacles redefined our educational strategies, turning failures into opportunities for improvement

    Function Biomedical Informatics Research Network Recommendations for Prospective Multi-Center Functional Magnetic Resonance Imaging Studies

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    This report provides practical recommendations for the design and execution of Multi-Center functional Magnetic Resonance Imaging (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The paper was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multi-site aspects include: (1) establishing and verifying scan parameters including scanner types and magnetic fields, (2) establishing and monitoring of a scanner quality program, (3) developing task paradigms and scan session documentation, (4) establishing clinical and scanner training to ensure consistency over time, (5) developing means for uploading, storing, and monitoring of imaging and other data, (6) the use of a traveling fMRI expert and (7) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery
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