60,324 research outputs found
The Open Research Web: A Preview of the Optimal and the Inevitable
The multiple online research impact metrics we are developing will allow the rich new database , the Research Web, to be navigated, analyzed, mined and evaluated in powerful new ways that were not even conceivable in the paper era – nor even in the online era, until the database and the tools became openly accessible for online use by all: by researchers, research institutions, research funders, teachers, students, and even by the general public that funds the research and for whose benefit it is being conducted: Which research is being used most? By whom? Which research is growing most quickly? In what direction? under whose influence? Which research is showing immediate short-term usefulness, which shows delayed, longer term usefulness, and which has sustained long-lasting impact? Which research and researchers are the most authoritative? Whose research is most using this authoritative research, and whose research is the authoritative research using? Which are the best pointers (“hubs”) to the authoritative research? Is there any way to predict what research will have later citation impact (based on its earlier download impact), so junior researchers can be given resources before their work has had a chance to make itself felt through citations? Can research trends and directions be predicted from the online database? Can text content be used to find and compare related research, for influence, overlap, direction? Can a layman, unfamiliar with the specialized content of a field, be guided to the most relevant and important work? These are just a sample of the new online-age questions that the Open Research Web will begin to answer
The organizational implications of medical imaging in the context of Malaysian hospitals
This research investigated the implementation and use of medical imaging in the
context of Malaysian hospitals. In this report medical imaging refers to PACS,
RIS/HIS and imaging modalities which are linked through a computer network. The
study examined how the internal context of a hospital and its external context
together influenced the implementation of medical imaging, and how this in turn
shaped organizational roles and relationships within the hospital itself. It further
investigated how the implementation of the technology in one hospital affected its
implementation in another hospital. The research used systems theory as the
theoretical framework for the study. Methodologically, the study used a case-based
approach and multiple methods to obtain data. The case studies included two
hospital-based radiology departments in Malaysia.
The outcomes of the research suggest that the implementation of medical imaging in
community hospitals is shaped by the external context particularly the role played by
the Ministry of Health. Furthermore, influences from both the internal and external
contexts have a substantial impact on the process of implementing medical imaging
and the extent of the benefits that the organization can gain. In the context of roles
and social relationships, the findings revealed that the routine use of medical
imaging has substantially affected radiographers’ roles, and the social relationships
between non clinical personnel and clinicians. This study found no change in the
relationship between radiographers and radiologists. Finally, the approaches to
implementation taken in the hospitals studied were found to influence those taken by
other hospitals.
Overall, this study makes three important contributions. Firstly, it extends Barley’s
(1986, 1990) research by explicitly demonstrating that the organization’s internal and
external contexts together shape the implementation and use of technology, that the
processes of implementing and using technology impact upon roles, relationships
and networks and that a role-based approach alone is inadequate to examine the
outcomes of deploying an advanced technology. Secondly, this study contends that
scalability of technology in the context of developing countries is not necessarily
linear. Finally, this study offers practical contributions that can benefit healthcare
organizations in Malaysia
Genetics of callous-unemotional behavior in children
Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU
Spartan Daily, March 19, 1997
Volume 108, Issue 39https://scholarworks.sjsu.edu/spartandaily/9114/thumbnail.jp
Acquiring Correct Knowledge for Natural Language Generation
Natural language generation (NLG) systems are computer software systems that
produce texts in English and other human languages, often from non-linguistic
input data. NLG systems, like most AI systems, need substantial amounts of
knowledge. However, our experience in two NLG projects suggests that it is
difficult to acquire correct knowledge for NLG systems; indeed, every knowledge
acquisition (KA) technique we tried had significant problems. In general terms,
these problems were due to the complexity, novelty, and poorly understood
nature of the tasks our systems attempted, and were worsened by the fact that
people write so differently. This meant in particular that corpus-based KA
approaches suffered because it was impossible to assemble a sizable corpus of
high-quality consistent manually written texts in our domains; and structured
expert-oriented KA techniques suffered because experts disagreed and because we
could not get enough information about special and unusual cases to build
robust systems. We believe that such problems are likely to affect many other
NLG systems as well. In the long term, we hope that new KA techniques may
emerge to help NLG system builders. In the shorter term, we believe that
understanding how individual KA techniques can fail, and using a mixture of
different KA techniques with different strengths and weaknesses, can help
developers acquire NLG knowledge that is mostly correct
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