76 research outputs found
On the asymptotic and approximate distributions of the product of an inverse Wishart matrix and a Gaussian vector
In this paper we study the distribution of the product of an inverse Wishart random matrix and a Gaussian random vector. We derive its asymptotic distribution as well as its approximate density function formula which is based on the Gaussian integral and the third order Taylor expansion. Furthermore, we compare obtained asymptotic and approximate density functions with the exact density which is obtained by Bodnar and Okhrin (2011). A good performance of obtained results is documented in the numerical study
Building RadiologyNET: Unsupervised annotation of a large-scale multimodal medical database
Background and objective: The usage of machine learning in medical diagnosis
and treatment has witnessed significant growth in recent years through the
development of computer-aided diagnosis systems that are often relying on
annotated medical radiology images. However, the availability of large
annotated image datasets remains a major obstacle since the process of
annotation is time-consuming and costly. This paper explores how to
automatically annotate a database of medical radiology images with regard to
their semantic similarity.
Material and methods: An automated, unsupervised approach is used to
construct a large annotated dataset of medical radiology images originating
from Clinical Hospital Centre Rijeka, Croatia, utilising multimodal sources,
including images, DICOM metadata, and narrative diagnoses. Several appropriate
feature extractors are tested for each of the data sources, and their utility
is evaluated using k-means and k-medoids clustering on a representative data
subset.
Results: The optimal feature extractors are then integrated into a multimodal
representation, which is then clustered to create an automated pipeline for
labelling a precursor dataset of 1,337,926 medical images into 50 clusters of
visually similar images. The quality of the clusters is assessed by examining
their homogeneity and mutual information, taking into account the anatomical
region and modality representation.
Conclusion: The results suggest that fusing the embeddings of all three data
sources together works best for the task of unsupervised clustering of
large-scale medical data, resulting in the most concise clusters. Hence, this
work is the first step towards building a much larger and more fine-grained
annotated dataset of medical radiology images
Climate-related land use policies in Brazil: How much has been achieved with economic incentives in agriculture?
Until 2019, the Brazilian federal government employed a number of policy measures to fulfill the pledge of reducing greenhouse gas emissions from land use change and agriculture. While its forest law enforcement strategy was partially successful in combating illegal deforestation, the effectiveness of positive incentive measures in agriculture has been less clear. The reason is that emissions reduction from market-based incentives such as the Brazilian Low-Carbon Agriculture Plan cannot be easily verified with current remote sensing monitoring approaches. Farmers have adopted a large variety of integrated land-use systems of crop, livestock and forestry with highly diverse per-hectare carbon balances. Their responses to policy incentives were largely driven by cost and benefit considerations at the farm level and not necessarily aligned with federal environmental objectives. This article analyzes climate-related land-use policies in the state of Mato Grosso, where highly mechanized soybean–cotton and soybean–maize cropping systems prevail. We employ agent-based bioeconomic simulation together with life-cycle assessment to explicitly capture the heterogeneity of farm-level costs, benefits of adoption, and greenhouse gas emissions. Our analysis confirms previous assessments but suggests a smaller farmer policy response when measured as increase in area of integrated systems. In terms of net carbon balances, our simulation results indicate that mitigation effects at the farm level depended heavily on the exact type of livestock and grazing system. The available data were insufficient to rule out even adverse effects. The Brazilian experience thus offers lessons for other land-rich countries that build their climate mitigation policies on economic incentives in agriculture
Quantification of coronary atherosclerotic burden with coronary computed tomography angiography: adapted Leaman score in Croatian patients
The aim of the study was to quantify the total coronary atherosclerotic burden in patients with suspected coronary artery disease (CAD) defined by coronary computed tomography adapted Leaman score (CT-LeSc) and to estimate its cut-off level for high coronary atherosclerotic burden. We enrolled 434 consecutive patients referred to coronary computed tomography angiography, of which 261 patients fulfilled the study inclusion criteria. Demographic and clinical characteristics, as well as CAD risk factors were obtained. CAD pre-test probabilities were estimated by the Diamond-Forrester model and Morise score. The coronary atherosclerotic burden was estimated using CT-LeSc. As a cut-off for a high coronary atherosclerotic burden, we used 3rd tercile (Tc3) (CT-LeSc ≥ 5.52). We evaluated the association of clinical characteristics and risk factors with Tc3 in univariate and multivariate analysis. There were 60.9% males and 39.1% females, 81% of patients had above-normal weight, 68.2% hypertension, 54.0% dyslipidemia, 15.3% diabetes mellitus, 12.3% positive smoking history and 11.9% had a family history of CAD. According to the Diamond-Forrester model and Morise score the majority of patients had intermediate risk, 59.7 and 52.8%, followed by the high-risk group, 36.0 and 34.4%, respectively. Age, dyslipidemia, hypertension and pre-test risk scores in the univariate analysis significantly predicted Tc3. In the multivariate analysis, male sex (p = 0.004), dyslipidemia (p = 0.002) and coronary calcium score (< 0.001) were identified as predictors of Tc3. CT-LeSc quantified the total coronary atherosclerotic burden and showed an association of risk factors and pre-test probabilities with Tc3
Ukradene shchasti︠e︡ : drama z silʹsʹkoho z︠h︡ytti︠a︡ v 5-okh dii︠a︡kh /
Mode of access: Internet
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