563 research outputs found
Overcoming the Legacy of Mistrust: African Americans’ Mistrust of Medical Profession
Recent studies show that racism still exists in the American medical profession, the fact of which legitimizes the historically long-legacy of mistrust towards medical profession and health authorities among African Americans. Thus, it was suspected that the participation of black patients in end-of-life care has always been significantly low stemmed primarily from their mistrust of the medical profession. On the other hand, much research finds that there are other reasons than the mistrust which makes African Americans feel reluctant to the end-of-life care, such as cultural-religious difference and genuine misunderstanding of the services. If so, two crucial questions are raised. One is how pervasive or significant the mistrust is, compared to the other factors, when they opt out of the end-of-life care. The other is if there is a remedy or solution to the seemingly broken relationship. While no studies available answer these questions, we have conducted an experiment to explore them. The research was performed at two Philadelphia hospitals of Mercy Health System, and the result shows that Black patients’ mistrust is not too great to overcome and that education can remove the epistemic obstacles as well as overcome the mistrust
Partially Conditioned Generative Adversarial Networks
Generative models are undoubtedly a hot topic in Artificial Intelligence,
among which the most common type is Generative Adversarial Networks (GANs).
These architectures let one synthesise artificial datasets by implicitly
modelling the underlying probability distribution of a real-world training
dataset. With the introduction of Conditional GANs and their variants, these
methods were extended to generating samples conditioned on ancillary
information available for each sample within the dataset. From a practical
standpoint, however, one might desire to generate data conditioned on partial
information. That is, only a subset of the ancillary conditioning variables
might be of interest when synthesising data. In this work, we argue that
standard Conditional GANs are not suitable for such a task and propose a new
Adversarial Network architecture and training strategy to deal with the ensuing
problems. Experiments illustrating the value of the proposed approach in digit
and face image synthesis under partial conditioning information are presented,
showing that the proposed method can effectively outperform the standard
approach under these circumstances.Comment: 10 pages, 9 figure
Locating Madhubani Painting in the Context of Cultural Tourism and Place Identity of Mithila Region
Art is often a reflection of culture and is considered to be the repository of a society’s collective memory. Researchers have long been interested in the relationship between art and culture. Art also has utilitarian influences on society and the times in which it is created in a cultural space is considered an integral component of culture. Different forms of art represent the diverse expressions of creative ideas in visual formats or performances that in turn, become an identity of a place. Madhubani paintings developed in the Mithilanchal region of Bihar are the perfect example of traditional art that maintained continuity through generations in the course of time and was assimilated gradually into the region's cultural setting. The tourism industry in India heavily banks on cultural tourism, and several communities have received a facelift by promoting places which are interesting for their heritage. Madhubani and nearby places in Bihar have a great tradition of paintings where visitors can find the authentic experience of these rich cultural features. The present study investigates the art tradition of Madhubani paintings, examining the challenges paused by commercialization and examining the scope of cultural tourism in the region.
 
Mismatch-based delayed thrombolysis: a meta-analysis
<p><b>Background and Purpose</b>: Clinical benefit from thrombolysis is reduced as stroke onset to treatment time increases. The use of "mismatch" imaging to identify patients for delayed treatment has face validity and has been used in case series and clinical trials. We undertook a meta-analysis of relevant trials to examine whether present evidence supports delayed thrombolysis among patients selected according to mismatch criteria.</p>
<p><b>Methods</b>: We collated outcome data for patients who were enrolled after 3 hours of stroke onset in thrombolysis trials and had mismatch on pretreatment imaging. We selected the trials on the basis of a systematic search of the Web of Knowledge. We compared favorable outcome, reperfusion and/or recanalization, mortality, and symptomatic intracerebral hemorrhage between the thrombolyzed and nonthrombolyzed groups of patients and the probability of a favorable outcome among patients with successful reperfusion and clinical findings for 3 to 6 versus 6 to 9 hours from poststroke onset. Results are expressed as adjusted odds ratios (a-ORs) with 95% CIs. Heterogeneity was explored by test statistics for clinical heterogeneity, I2 (inconsistency), and L’Abbé plot.</p>
<p><b>Results</b>: We identified articles describing the DIAS, DIAS II, DEDAS, DEFUSE, and EPITHET trials, giving a total of 502 mismatch patients thrombolyzed beyond 3 hours. The combined a-ORs for favorable outcomes were greater for patients who had successful reperfusion (a-OR=5.2; 95% CI, 3 to 9; I2=0%). Favorable clinical outcome was not significantly improved by thrombolysis (a-OR=1.3; 95% CI, 0.8 to 2.0; I2=20.9%). Odds for reperfusion/recanalization were increased among patients who received thrombolytic therapy (a-OR=3.0; 95% CI, 1.6 to 5.8; I2=25.7%). The combined data showed a significant increase in mortality after thrombolysis (a-OR=2.4; 95% CI, 1.2 to 4.9; I2=0%), but this was not confirmed when we excluded data from desmoteplase doses that were abandoned in clinical development (a-OR=1.6; 95% CI, 0.7 to 3.7; I2=0%). Symptomatic intracerebral hemorrhage was significantly increased after thrombolysis (a-OR=6.5; 95% CI, 1.2 to 35.4; I2=0%) but not significant after exclusion of abandoned doses of desmoteplase (a-OR=5.4; 95% CI, 0.9 to 31.8; I2=0%).</p>
<p><b>Conclusions</b>: Delayed thrombolysis amongst patients selected according to mismatch imaging is associated with increased reperfusion/recanalization. Recanalization/reperfusion is associated with improved outcomes. However, delayed thrombolysis in mismatch patients was not confirmed to improve clinical outcome, although a useful clinical benefit remains possible. Thrombolysis carries a significant risk of symptomatic intracerebral hemorrhage and possibly increased mortality. Criteria to diagnose mismatch are still evolving. Validation of the mismatch selection paradigm is required with a phase III trial. Pending these results, delayed treatment, even according to mismatch selection, cannot be recommended as part of routine care.</p>
Role of social environment and social clustering in spread of opinions in co-evolving networks
Taking a pragmatic approach to the processes involved in the phenomena of
collective opinion formation, we investigate two specific modifications to the
co-evolving network voter model of opinion formation, studied by Holme and
Newman [1]. First, we replace the rewiring probability parameter by a
distribution of probability of accepting or rejecting opinions between
individuals, accounting for the asymmetric influences in relationships among
individuals in a social group. Second, we modify the rewiring step by a
path-length-based preference for rewiring that reinforces local clustering. We
have investigated the influences of these modifications on the outcomes of the
simulations of this model. We found that varying the shape of the distribution
of probability of accepting or rejecting opinions can lead to the emergence of
two qualitatively distinct final states, one having several isolated connected
components each in internal consensus leading to the existence of diverse set
of opinions and the other having one single dominant connected component with
each node within it having the same opinion. Furthermore, and more importantly,
we found that the initial clustering in network can also induce similar
transitions. Our investigation also brings forward that these transitions are
governed by a weak and complex dependence on system size. We found that the
networks in the final states of the model have rich structural properties
including the small world property for some parameter regimes. [1] P. Holme and
M. Newman, Phys. Rev. E 74, 056108 (2006)
Social clustering in epidemic spread on coevolving networks
Even though transitivity is a central structural feature of social networks, its influence on epidemic spread on coevolving networks has remained relatively unexplored. Here we introduce and study an adaptive susceptible- infected-susceptible (SIS) epidemic model wherein the infection and network coevolve with nontrivial proba- bility to close triangles during edge rewiring, leading to substantial reinforcement of network transitivity. This model provides an opportunity to study the role of transitivity in altering the SIS dynamics on a coevolving network. Using numerical simulations and approximate master equations (AMEs), we identify and examine a rich set of dynamical features in the model. In many cases, AMEs including transitivity reinforcement provide accurate predictions of stationary-state disease prevalence and network degree distributions. Furthermore, for some parameter settings, the AMEs accurately trace the temporal evolution of the system. We show that higher transitivity reinforcement in the model leads to lower levels of infective individuals in the population, when closing a triangle is the dominant rewiring mechanism. These methods and results may be useful in developing ideas and modeling strategies for controlling SIS-type epidemics
Tricuspid annular plane systolic excursion (TAPSE) revisited using CMR
This observational pilot project was performed as background to eventually create a rapid, automated and accurate assessment of RV systolic function in variable clinical subgroups. We propose new parameters that characterize the global systolic function of the right ventricle with a simple linear measurement
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