38,734 research outputs found
Translating Research Into Practice: Speeding the Adoption of Innovative Health Care Programs
Looks at case studies of four innovative clinical programs to determine key factors influencing the diffusion and adoption of innovations in health care
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The LONI QC System: A Semi-Automated, Web-Based and Freely-Available Environment for the Comprehensive Quality Control of Neuroimaging Data.
Quantifying, controlling, and monitoring image quality is an essential prerequisite for ensuring the validity and reproducibility of many types of neuroimaging data analyses. Implementation of quality control (QC) procedures is the key to ensuring that neuroimaging data are of high-quality and their validity in the subsequent analyses. We introduce the QC system of the Laboratory of Neuro Imaging (LONI): a web-based system featuring a workflow for the assessment of various modality and contrast brain imaging data. The design allows users to anonymously upload imaging data to the LONI-QC system. It then computes an exhaustive set of QC metrics which aids users to perform a standardized QC by generating a range of scalar and vector statistics. These procedures are performed in parallel using a large compute cluster. Finally, the system offers an automated QC procedure for structural MRI, which can flag each QC metric as being 'good' or 'bad.' Validation using various sets of data acquired from a single scanner and from multiple sites demonstrated the reproducibility of our QC metrics, and the sensitivity and specificity of the proposed Auto QC to 'bad' quality images in comparison to visual inspection. To the best of our knowledge, LONI-QC is the first online QC system that uniquely supports the variety of functionality where we compute numerous QC metrics and perform visual/automated image QC of multi-contrast and multi-modal brain imaging data. The LONI-QC system has been used to assess the quality of large neuroimaging datasets acquired as part of various multi-site studies such as the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Study and the Alzheimer's Disease Neuroimaging Initiative (ADNI). LONI-QC's functionality is freely available to users worldwide and its adoption by imaging researchers is likely to contribute substantially to upholding high standards of brain image data quality and to implementing these standards across the neuroimaging community
Game Changer: Investing in Digital Play to Advance Children's Learning and Health
Based on a literature review and interviews with digital learning experts, explores how digital games can foster skills and knowledge for better academic performance and health. Makes recommendations for government research, partnerships, and media
State of the art: iterative CT reconstruction techniques
Owing to recent advances in computing power, iterative reconstruction (IR) algorithms have become a clinically viable option in computed tomographic (CT) imaging. Substantial evidence is accumulating about the advantages of IR algorithms over established analytical methods, such as filtered back projection. IR improves image quality through cyclic image processing. Although all available solutions share the common mechanism of artifact reduction and/or potential for radiation dose savings, chiefly due to image noise suppression, the magnitude of these effects depends on the specific IR algorithm. In the first section of this contribution, the technical bases of IR are briefly reviewed and the currently available algorithms released by the major CT manufacturers are described. In the second part, the current status of their clinical implementation is surveyed. Regardless of the applied IR algorithm, the available evidence attests to the substantial potential of IR algorithms for overcoming traditional limitations in CT imaging
A Virtual Conversational Agent for Teens with Autism: Experimental Results and Design Lessons
We present the design of an online social skills development interface for
teenagers with autism spectrum disorder (ASD). The interface is intended to
enable private conversation practice anywhere, anytime using a web-browser.
Users converse informally with a virtual agent, receiving feedback on nonverbal
cues in real-time, and summary feedback. The prototype was developed in
consultation with an expert UX designer, two psychologists, and a pediatrician.
Using the data from 47 individuals, feedback and dialogue generation were
automated using a hidden Markov model and a schema-driven dialogue manager
capable of handling multi-topic conversations. We conducted a study with nine
high-functioning ASD teenagers. Through a thematic analysis of post-experiment
interviews, identified several key design considerations, notably: 1) Users
should be fully briefed at the outset about the purpose and limitations of the
system, to avoid unrealistic expectations. 2) An interface should incorporate
positive acknowledgment of behavior change. 3) Realistic appearance of a
virtual agent and responsiveness are important in engaging users. 4)
Conversation personalization, for instance in prompting laconic users for more
input and reciprocal questions, would help the teenagers engage for longer
terms and increase the system's utility
Healthy Steps at 15: The Past and Future of an Innovative Preventive Care Model for Young Children
Evaluates a model for preventive pediatric care for children up to age 3 that relies on mid-level specialists, including the program's spread, operating costs, funding, challenges, and potential effects of healthcare reform. Includes site profiles
Interactions between species introduce spurious associations in microbiome studies
Microbiota contribute to many dimensions of host phenotype, including
disease. To link specific microbes to specific phenotypes, microbiome-wide
association studies compare microbial abundances between two groups of samples.
Abundance differences, however, reflect not only direct associations with the
phenotype, but also indirect effects due to microbial interactions. We found
that microbial interactions could easily generate a large number of spurious
associations that provide no mechanistic insight. Using techniques from
statistical physics, we developed a method to remove indirect associations and
applied it to the largest dataset on pediatric inflammatory bowel disease. Our
method corrected the inflation of p-values in standard association tests and
showed that only a small subset of associations is directly linked to the
disease. Direct associations had a much higher accuracy in separating cases
from controls and pointed to immunomodulation, butyrate production, and the
brain-gut axis as important factors in the inflammatory bowel disease.Comment: 4 main text figures, 15 supplementary figures (i.e appendix) and 6
supplementary tables. Overall 49 pages including reference
Ergonomics of the Operative Field in Paediatric Minimal Access Surgery
Imperial Users onl
The OCarePlatform : a context-aware system to support independent living
Background: Currently, healthcare services, such as institutional care facilities, are burdened with an increasing number of elderly people and individuals with chronic illnesses and a decreasing number of competent caregivers. Objectives: To relieve the burden on healthcare services, independent living at home could be facilitated, by offering individuals and their (in)formal caregivers support in their daily care and needs. With the rise of pervasive healthcare, new information technology solutions can assist elderly people ("residents") and their caregivers to allow residents to live independently for as long as possible. Methods: To this end, the OCarePlatform system was designed. This semantic, data-driven and cloud based back-end system facilitates independent living by offering information and knowledge-based services to the resident and his/her (in)formal caregivers. Data and context information are gathered to realize context-aware and personalized services and to support residents in meeting their daily needs. This body of data, originating from heterogeneous data and information sources, is sent to personalized services, where is fused, thus creating an overview of the resident's current situation. Results: The architecture of the OCarePlatform is proposed, which is based on a service-oriented approach, together with its different components and their interactions. The implementation details are presented, together with a running example. A scalability and performance study of the OCarePlatform was performed. The results indicate that the OCarePlatform is able to support a realistic working environment and respond to a trigger in less than 5 seconds. The system is highly dependent on the allocated memory. Conclusion: The data-driven character of the OCarePlatform facilitates easy plug-in of new functionality, enabling the design of personalized, context-aware services. The OCarePlatform leads to better support for elderly people and individuals with chronic illnesses, who live independently. (C) 2016 Elsevier Ireland Ltd. All rights reserved
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