LAUSR

Sequential feature selection and inference using multi‐variate random forests

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0 Published in 2018 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btx784

Abstract: Motivation Random forest (RF) has become a widely popular prediction generating mechanism. Its strength lies in its flexibility, interpretability and ability to handle large number of features, typically larger than the sample size. However, this… read more here.

Keywords: methodology; feature selection; multi variate; selection ... See more keywords

SNR-Adaptive OCT Angiography Enabled by Statistical Characterization of Intensity and Decorrelation With Multi-Variate Time Series Model

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0 Published in 2019 at "IEEE Transactions on Medical Imaging"

DOI: 10.1109/tmi.2019.2910871

Abstract: In OCT angiography (OCTA), decorrelation computation has been widely used as a local motion index to identify dynamic flow from static tissues, but its dependence on SNR severely degrades the vascular visibility, particularly in low-SNR… read more here.

Keywords: oct; multi variate; oct angiography; model ... See more keywords

A Multi-Variate Approach to Predicting Myoelectric Control Usability

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0 Published in 2021 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"

DOI: 10.1109/tnsre.2021.3094324

Abstract: Pattern recognition techniques leveraging the use of electromyography signals have become a popular approach to provide intuitive control of myoelectric devices. Performance of these control interfaces is commonly quantified using offline classification accuracy, despite studies… read more here.

Keywords: control; variate approach; offline metrics; multi variate ... See more keywords

Feature Level-Sets: Generalizing Iso-Surfaces to Multi-Variate Data

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0 Published in 2020 at "IEEE Transactions on Visualization and Computer Graphics"

DOI: 10.1109/tvcg.2018.2867488

Abstract: Iso-surfaces or level-sets provide an effective and frequently used means for feature visualization. However, they are restricted to simple features for uni-variate data. The approach does not scale when moving to multi-variate data or when… read more here.

Keywords: level sets; feature level; iso surfaces; multi variate ... See more keywords

A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records

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0 Published in 2019 at "BMC Medical Informatics and Decision Making"

DOI: 10.1186/s12911-018-0717-4

Abstract: BackgroundAdverse drug events (ADEs) as well as other preventable adverse events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in the United States alone. Therefore, it is of paramount importance… read more here.

Keywords: temporal features; framework; multi variate; classification framework ... See more keywords

National Holidays and Social Mobility Behaviors: Alternatives for Forecasting COVID-19 Deaths in Brazil

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0 Published in 2021 at "International Journal of Environmental Research and Public Health"

DOI: 10.3390/ijerph182111595

Abstract: In this paper, we investigate the influence of holidays and community mobility on the transmission rate and death count of COVID-19 in Brazil. We identify national holidays and hallmark holidays to assess their effect on… read more here.

Keywords: mobility; multi variate; variate model; national holidays ... See more keywords

Certain Properties and Applications of Convoluted Δh Multi-Variate Hermite and Appell Sequences

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1 Published in 2023 at "Symmetry"

DOI: 10.3390/sym15040828

Abstract: This study follows the line of research that by employing the monomiality principle, new outcomes are produced. Thus, in line with prior facts, our aim is to introduce the Δh multi-variate Hermite Appell polynomials ΔhHAm[r](q1,q2,⋯,qr;h).… read more here.

Keywords: hermite appell; multi variate; variate hermite;

Multi-variate factorisation of numerical simulations

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0 Published in 2021 at "Geoscientific Model Development"

DOI: 10.5194/gmd-14-4307-2021

Abstract: Abstract. Factorisation (also known as “factor separation”) is widely used in the analysis of numerical simulations. It allows changes in properties of a system to be attributed to changes in multiple variables associated with that… read more here.

Keywords: numerical simulations; multi variate; factorisation numerical; factorisation ... See more keywords