Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction
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Using data from student use of educational technologies to evaluate and improve cognitive models of learners is now a common approach in EDM. Such naturally occurring data poses modeling challenges when non-random factors drive what data is collected. Prio ...
Purpose: Most effective antitumor therapies induce tumor cell death. Non-invasive, rapid and accurate quantitative imaging of cell death is essential for monitoring early response to antitumor therapies. To facilitate this, we previously developed a biocom ...
Selection and aggregation of ranking criteria became an important topic in information retrieval as search is getting more specialized and as volume of electronically available information grows. In this context, document ranking has undergone a shift from ...
Although numerous positron emission tomography (PET) studies with ((8) F-fluoro-deoxyglucose) FDG have reported quantitative results on cerebral glucose kinetics and consumption, there is a large variation between the absolute values found in the literatur ...
Background: One of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted genomic data. More precisely, given a list of approximately 1500 patient records, each with 18 binary feat ...
Complexity is a double-edged sword for learning algorithms when the number of available samples for training in relation to the dimension of the feature space is small. This is because simple models do not sufficiently capture the nuances of the data set, ...
This paper proposes a distributionally robust approach to logistic regression. We use the Wasserstein distance to construct a ball in the space of probability distributions centered at the uniform distribution on the training samples. If the radius of this ...
Convolutional Neural Networks (CNNs) have been widely adopted for many imaging applications. For image aesthetics prediction, state-of-the-art algorithms train CNNs on a recently-published large-scale dataset, AVA. However, the distribution of the aestheti ...
Accurate assessment of mice cardiac function with magnetic resonance imaging is essential for longitudinal studies and for drug development related to cardiovascular diseases. Whereas dedicated small animal MR scanners are not readily available, it would b ...
We consider inference on a vector-valued parameter of interest in a linear exponential family, in the presence of a finite-dimensional nuisance parameter. Based on higher-order asymptotic theory for likelihood, we propose a directional test whose p-value i ...