GridIMAGE: A Novel Use of Grid Computing to Support Interactive Human and Computer-Assisted Detection Decision Support

This paper describes a Grid-aware image reviewing system (GridIMAGE) that allows practitioners to (a) select images from multiple geographically distributed digital imaging and communication in medicine (DICOM) servers, (b) send those images to a specified group of human readers and computer-assisted detection (CAD) algorithms, and (c) obtain and compare interpretations from human readers and CAD algorithms. The currently implemented system was developed using the National Cancer Institute caGrid infrastructure and is designed to support the identification of lung nodules on thoracic computed tomography. However, the infrastructure is general and can support any type of distributed review. caGrid data and analytical services are used to link DICOM image databases and CAD systems and to interact with human readers. Moreover, the service-oriented and distributed structure of the GridIMAGE framework enables a flexible system, which can be deployed in an institution (linking multiple DICOM servers and CAD algorithms) and in a Grid environment (linking the resources of collaborating research groups). GridIMAGE provides a framework that allows practitioners to obtain interpretations from one or more human readers or CAD algorithms. It also provides a mechanism to allow cooperative imaging groups to systematically perform image interpretation tasks associated with research protocols

e-Science and biological pathway semantics

<p>Abstract</p> <p>Background</p> <p>The development of e-Science presents a major set of opportunities and challenges for the future progress of biological and life scientific research. Major new tools are required and corresponding demands are placed on the high-throughput data generated and used in these processes. Nowhere is the demand greater than in the semantic integration of these data. Semantic Web tools and technologies afford the chance to achieve this semantic integration. Since pathway knowledge is central to much of the scientific research today it is a good test-bed for semantic integration. Within the context of biological pathways, the BioPAX initiative, part of a broader movement towards the standardization and integration of life science databases, forms a necessary prerequisite for its successful application of e-Science in health care and life science research. This paper examines whether BioPAX, an effort to overcome the barrier of disparate and heterogeneous pathway data sources, addresses the needs of e-Science.</p> <p>Results</p> <p>We demonstrate how BioPAX pathway data can be used to ask and answer some useful biological questions. We find that BioPAX comes close to meeting a broad range of e-Science needs, but certain semantic weaknesses mean that these goals are missed. We make a series of recommendations for re-modeling some aspects of BioPAX to better meet these needs.</p> <p>Conclusion</p> <p>Once these semantic weaknesses are addressed, it will be possible to integrate pathway information in a manner that would be useful in e-Science.</p

The FAIR Guiding Principles for scientific data management and stewardship

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community

Neural correlates of positive and negative performance feedback in younger and older adults

BACKGROUND: Recent studies with younger adults have shown that performance feedback can serve as a reward, and it elicits reward-related brain activations. This study investigated whether performance feedback is processed similarly in younger and older adults and whether there are differential aging effects for positive and negative performance feedback. METHODS: We used event-related fMRI in a choice reaction-time task and provided performance feedback after each trial. RESULTS: Although younger and older adults differed in task-related activation, they showed comparable reward-related activation. Positive performance feedback elicited the strongest striatal and amygdala activation, which was reflected behaviorally in slightly faster reaction times. CONCLUSIONS: These results suggest that performance feedback serves as a reward in both younger and older adults

A data citation roadmap for scholarly data repositories

This article presents a practical roadmap for scholarly data repositories to implement data citation in accordance with the Joint Declaration of Data Citation Principles, a synopsis and harmonization of the recommendations of major science policy bodies. The roadmap was developed by the Repositories Expert Group, as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH-funded BioCADDIE (https://biocaddie.org) project. The roadmap makes 11 specific recommendations, grouped into three phases of implementation: a) required steps needed to support the Joint Declaration of Data Citation Principles, b) recommended steps that facilitate article/data publication workflows, and c) optional steps that further improve data citation support provided by data repositories. We describe the early adoption of these recommendations 18 months after they have first been published, looking specifically at implementations of machine-readable metadata on dataset landing pages

Finding useful data across multiple biomedical data repositories using DataMed

The value of broadening searches for data across multiple repositories has been identified by the biomedical research community. As part of the NIH Big Data to Knowledge initiative, we work with an international community of researchers, service providers and knowledge experts to develop and test a data index and search engine, which are based on metadata extracted from various datasets in a range of repositories. DataMed is designed to be, for data, what PubMed has been for the scientific literature. DataMed supports Findability and Accessibility of datasets. These characteristics - along with Interoperability and Reusability - compose the four FAIR principles to facilitate knowledge discovery in today’s big data-intensive science landscape

VirtualPACS—A Federating Gateway to Access Remote Image Data Resources over the Grid

Collaborations in biomedical research and clinical studies require that data, software, and computational resources be shared between geographically distant institutions. In radiology, there is a related issue of sharing remote DICOM data over the Internet. This paper focuses on the problem of federating multiple image data resources such that clients can interact with them as if they are stored in a centralized PACS. We present a toolkit, called VirtualPACS, to support this functionality. Using the toolkit, users can perform standard DICOM operations (query, retrieve, and submit) across distributed image databases. The key features of the toolkit are: (1) VirtualPACS makes it easy to use existing DICOM client applications for data access; (2) it can easily be incorporated into an imaging workflow as a DICOM source; (3) using VirtualPACS, heterogeneous collections of DICOM sources are exposed to clients through a uniform interface and common data model; and (4) DICOM image databases without DICOM messaging can be accessed