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UMCCTS Newsletter, September 2016

Fri, 09/30/2016 - 8:24am

This is the September 2016 issue of the UMass Center for Clinical and Translational Science Newsletter containing news and events of interest.

UMCCTS Newsletter, August 2016

Fri, 09/30/2016 - 8:24am

This is the August 2016 issue of the UMass Center for Clinical and Translational Science Newsletter containing news and events of interest.

UMCCTS Newsletter, July 2016

Fri, 09/30/2016 - 8:24am

This is the July 2016 issue of the UMass Center for Clinical and Translational Science Newsletter containing news and events of interest.

UMCCTS Newsletter, June 2016

Fri, 09/30/2016 - 8:24am

This is the June 2016 issue of the UMass Center for Clinical and Translational Science Newsletter containing news and events of interest.

UMCCTS Newsletter, May 2016

Fri, 09/30/2016 - 8:24am

This is the May 2016 issue of the UMass Center for Clinical and Translational Science Newsletter containing news and events of interest.

Treatment of Cancer Pain

Fri, 09/30/2016 - 7:20am

Pain is one of the first concerns most cancer patients express when newly diagnosed or meeting a new physician. They are concerned about how much pain they presently have, how much pain they are likely to experience, and their physicians’ commitment to treating cancer pain. The reality is that many cancer patients will never experience pain during their course and for those that do, the great majority can be well-managed with the tools described in this chapter in Cancer Concepts: A Guidebook for the Non-Oncologist. It is incumbent on every physician to understand the mechanisms of cancer pain and the fundamentals of treating it.

Data Citation in Neuroimaging: Proposed Best Practices for Data Identification and Attribution

Thu, 09/29/2016 - 10:28am

Data sharing and reuse, while widely accepted as good ideas, have been slow to catch on in any concrete and consistent way. One major hurdle within the scientific community has been the lack of widely accepted standards for citing that data, making it difficult to track usage and measure impact. Within the neuroimaging community, there is a need for a way to not only clearly identify and cite datasets, but also to derive new aggregate sets from multiple sources while clearly maintaining lines of attribution. This work presents a functional prototype of a system to integrate Digital Object Identifiers (DOI) and a standardized metadata schema into a XNAT-based repository workflow, allowing for identification of data at both the project and image level. These item and source level identifiers allow any newly defined combination of images, from any number of projects, to be tagged with a new group-level DOI that automatically inherits the individual attributes and provenance information of its constituent parts. This system enables the tracking of data reuse down to the level of individual images. The implementation of this type of data identification system would impact researchers and data creators, data hosting facilities, and data publishers, but the benefit of having widely accepted standards for data identification and attribution would go far toward making data citation practical and advantageous.