Introduction to Real Life Data
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Real Life Data sentence examples within extensive experimental evaluation
Our extensive experimental evaluation using both synthetic and real-life data sets and workloads shows that (a) the Adaptive KD-Tree reduces total workload time by up to a factor 2 compared to the state-of-the-art, (b) the Progressive KD-Tree achieves predictable convergence with up to one order of magnitude lower initial query cost, and (c) the Greedy Progressive KDTree exhibits the lowest query variance up to three orders of magnitude lower than the state-of-the-art.
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In an extensive experimental evaluation using two real-life datasets, we show that our novel techniques are indeed capable of producing clustering solutions that are more justifiable without a substantial negative impact on their quality.
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Real Life Data sentence examples within post discharge early
To explore predictors of in-hospital mortality (IHM), post discharge early mortality [1-month mortality (1mM)] and late mortality [1-year mortality (1yM)] and early and late readmission, respectively 1-month readmission (1mRA) and 1-year readmission (1yRA), in our center population, using real-life data.
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To validate ACTION-ICU score in AHF as predictor of in-hospital M (IHM), post discharge early M [1-month mortality (1mM)] and 1-month readmission (1mRA), in our center population, using real-life data.
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Real Life Data sentence examples within 1 month mortality
To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data.
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Real Life Data sentence examples within soft β rough
Soft rough set theory has been presented as a basic mathematical model for decision-making for many real-life data However, soft rough sets are based on a possible fusion of rough sets and soft sets which were proposed by Feng et al [20] The main contribution of the present article is to introduce a modification and a generalization for Feng's approximations, namely, soft β -rough approximations, and some of their properties will be studied A comparison between the suggested approximations and the previous one [20] will be discussed Some examples are prepared to display the validness of these proposals Finally, we put an actual example of the infections of coronavirus (COVID-19) based on soft β -rough sets This application aims to know the persons most likely to be infected with COVID-19 via soft β -rough approximations and soft β -rough topologies [ABSTRACT FROM AUTHOR] Copyright of Turkish Journal of Mathematics is the property of Scientific and Technical Research Council of Turkey and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all s ).
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Real Life Data sentence examples within Two Real Life Data
Our claims are validated by experiments on two real life data sets, the public domain Epinions.
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In practice, experiments conducted over two real life datasets also could demonstrate the significant superiority of IRAI, which could provide high performance in real life applications.
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Real Life Data sentence examples within Three Real Life Data
Real Life Data sentence examples within Some Real Life Data
Some real life data has been used to get approximate PH representations for channel idle and busy period variates, which in turn are used for numerical illustrations.
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Some real life data like human gene have an inherent structure of hierarchy, which embeds multi-layer feature groups.
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Real Life Data sentence examples within Certain Real Life Data
We discuss the estimation of parameters of the location-scale extended class of DLD and illustrate the procedures with the help of certain real life data sets.
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Our method is simple in comparison to known methods, and gives good enough estimates to make it useful in certain real life datasets that arise in data mining scenarios.
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Real Life Data sentence examples within Collecting Real Life Data
Since the dataset requires videos recorded using thermal camera of gas leakage, collecting real life data has its own barriers (safety reason, availability, etc.
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Since the dataset requires videos recorded using thermal camera of gas leakage, collecting real life data has its own barriers (safety reason, availability, etc.
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Real Life Data sentence examples within real life data set
Real Life Data sentence examples within real life data example
Our simulations on a real-life dataset shows that pelte can accurately predict privacy settings even when a user has shared a few images with others, the images have only a few tags or the user’s friends have varying privacy preferences.
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To compare the clinical and laboratory findings of multisystem inflammatory syndrome in children (MIS-C), patients with Kawasaki disease (KD) and with macrophage activating syndrome due to systemic juvenile idiopathic arthritis (sJIA-MAS) on real-life data.
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However, these studies have remained at the level of proposals without validation on real-life datasets or they have only considered one metaheuristic in isolation.
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Extensive performance analyses of all the algorithms are observed over several real-life datasets and impressive results are found compared to the existing research.
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However, little real-life data have been reported on its use in the elderly population.
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An experiment is conducted on a real-life dataset Foursquare, of which the result shows it improves top-1 accuracy by 12.
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Using real-life datasets and GNN models GCN, PinSage and MAGNN, we verify that NAU makes FlexGraph more expressive than prior frameworks (e.
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To explore predictors of in-hospital mortality (IHM), post discharge early mortality [1-month mortality (1mM)] and late mortality [1-year mortality (1yM)] and early and late readmission, respectively 1-month readmission (1mRA) and 1-year readmission (1yRA), in our center population, using real-life data.
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Dealing with uncertainty in applications of machine learning to real-life data critically depends on the knowledge of intrinsic dimensionality (ID).
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This research uses real-life data of an international fashion retailer.
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One real-life data set is analyzed to illustrate the evaluation of proposed methods of estimation.
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tn (by using real-life datasets from anti-leprosy vaccine trial conducted in south India).
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The model is verified through the case study with the real-life data originating from a significant number of organizations from one region.
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Besides, comparative studies with previous publications and real-life data analysis are carried out to illustrate the robustness and practicability of the models and strategies.
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BACKGROUND
There are limited real-life data on isavuconazole prophylaxis and treatment of invasive mold infections (IMI) in hematological patients and allogeneic hematopoietic cell transplant (HCT) recipients.
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Since then few real-life data are available.
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A simulation study based on selected hypothetical distributions and a real-life data set showed that IPRSS is more precise than RSS, Paired RSS (PRSS) or Extreme RSS (ERSS).
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We allow a mixed uncertain environment by considering uncertain-random parameters in the proposed model to express ambiguity in real-life data.
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OBJECTIVES
To report real-life data on the use of DTG-based dual therapies in treatment-experienced patients.
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Context: Real-life data consist of exhaustive and unbiased data to study drug-safety profiles but are underused because of their complex temporality (i.
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These classification algorithms are not always efficient when it comes to real-life datasets due to class distributions.
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But the real-life data does not follow such a rule properly in various domains.
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Objectives: To depict contemporary real-life data regarding the work-related burden of disease among Greek patients with RD.
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We use the nascent decentralized insurance market as a laboratory to apply our model based on real-life data and show that relatively small stakes are sufficient to maximize network throughput, which is equivalent to welfare.
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Extensive simulations over both synthetic and real-life datasets are conducted to confirm the efficiency of all proposed schemes.
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Initial real-life data suggest variable degree of adherence with higher adherence resulting in reduced adverse outcomes.
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Actigraphy has the ability to collect real-life data without interfering with clinical practice and give clinicians a new measure of performance that is currently not available.
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The applications of the new WIR distribution were demonstrated on three real-life data sets.
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The real-life data application is also a part of this study.
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The usefulness of the new model is illustrated by means of three real-life data sets.
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We demonstrate the performance of our approach to real-life data of two cell lines, human osteosarcoma and human leukemia, collected at the University of Amsterdam (133 training images, and 32 test images).
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Our proposed framework was trained and evaluated using a real-life dataset of users interacting spontaneously with a social robot in a dynamic environment.
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However, using real-life training data alone or in combination with semi-structured data generated better results for older adults who had high real-life data quality.
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In our real-life data study, the median onset time of grade III-IV irAES was 128 days after the initiation of immune checkpoint inhibitors (ICI) therapy.
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Finally, we experimentally evaluate and compare the scalability and accuracy of our approaches on several real-life datasets.
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Experiments on real-life datasets of 4 cities demonstrate that PSRNet has significant advantages over 8 baselines by reducing RMSE and MAE for more than 25%.
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The numerical results based on real-life data sets show that the proposed method can achieve high predicted accuracy of BP while saving training time.
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We verify the effectiveness of PC-TD on real-life datasets.
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The aims of this study were to provide real-life data about the effect of COVID-19 pandemic on the practice of anti-VEGF injections and to evaluate the safety of the modifications in the injection protocol imposed during the ongoing pandemic on the anatomical and functional outcome of patients.
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Two real-life datasets were used to evaluate the model’s performance compared to the previous related works.
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Extensive experiments based on real-life datasets demonstrate that the proposed method achieves higher accuracy than several typical baseline methods.
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The study aimed to compare the prolonged cytopenias depending on fitness and report real-life data on dose reduction measures and efficacy.
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Experimental results on real-life datasets show that SMoTAS not only achieves substantial improvement of accuracy over existing methods in discovering significant places, but also exhibits superior adaptability to different trajectories and application scenarios.
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The purpose of our study was to present real-life data of chronic hepatitis C (CHC) infected patients with genotypes 2 and 3 who were treated with glecaprevir/pibrentasvir regimen.
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Findings
This study trains the model using a real-life data set extracted based on Twitter follower/followee architecture.
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Experimental results on three real-life datasets show that our approach achieves better performance and outperforms previous non-pretrained methods on the ZS-MTC task.
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Real-life data and head-to-head clinical trials will be needed to confirm its efficacy and safety.
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However, real-life data and long-term survival data are lacking.
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Vaccination has been proven to be the crucial pillar for preventing asymptomatic infections and real-life data will continue to exhibit the effects of community vaccination in breaking the transmission chain of SARS-CoV-2 infections.
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However, these examples are not based on real-life data since the lack of parameter estimation method for fuzzy differential equation driven by Liu process.
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The methods are applied to real-life data from a call centre and the results show improvements in the achieved service level and a significant drop in the number of abandoned calls.