Results 41 to 50 of about 185,151 (349)
BMC Bioinformatics, 2021 Background Atrial fibrillation is a paroxysmal heart disease without any obvious symptoms for most people during the onset. The electrocardiogram (ECG) at the time other than the onset of this disease is not significantly different from that of normal ...
Cai Wu +8 more
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, 2000 This chapter contains sections titled: Introduction, Boosting and the Linear Programming Solution, υ-Algorithms, Experiments, Conclusion, Acknowledgments.
Raetsch, Gunnar +5 more
openaire +3 more sources
Modulation of Homer1 EVH1 domain internal dynamics by putative autism‐associated mutations
FEBS Letters, EarlyView.The putative autism‐associated M65I and S97L variants of the EVH1 domain of the postsynaptic scaffold protein Homer1 do not exhibit substantial changes in their overall structure or partner binding. Both of them, but especially the M65I variant, show altered internal dynamics relative to the wild‐type domain on the μs‐ms timescale, indicated by the ...
Fanni Farkas +6 more
wiley +1 more source
Ensemble Techniques Based Risk Classification for Maternal Health During Pregnancy
Ilkom Jurnal IlmiahThis research focuses on the critical aspect of maternal health during pregnancy, emphasizing the need for early detection and intervention to address potential risks to both mothers and infants. Leveraging various classification methods, including Naïve
Nurul Fathanah Mustamin +3 more
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Interpreting the effects of DNA polymerase variants at the structural level
Molecular Oncology, EarlyView.Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Neural network ensemble operators for time series forecasting [PDF]
, 2014 The combination of forecasts resulting from an ensemble of neural networks has been shown to outperform the use of a single ``best'' network model.
Barrow, Devon K.; id_orcid +8 more
core +1 more source
Diverse Models, United Goal: A Comprehensive Survey of Ensemble Learning
CAAI Transactions on Intelligence TechnologyEnsemble learning, a pivotal branch of machine learning, amalgamates multiple base models to enhance the overarching performance of predictive models, capitalising on the diversity and collective wisdom of the ensemble to surpass individual models and ...
Ziwei Fan +7 more
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PLoS ONE, 2019 Simulator imperfection, often known as model error, is ubiquitous in practical data assimilation problems. Despite the enormous efforts dedicated to addressing this problem, properly handling simulator imperfection in data assimilation remains to be a ...
Xiaodong Luo
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Agronomy, 2023 This study employed an ensemble machine learning approach to evaluate the effect of bioclimatic covariates on the prediction accuracy of soil total carbon (TC) in the Pannonian biogeoregion. The analysis involved two main segments: (1) evaluation of base
Dorijan Radočaj +2 more
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FEBS Open Bio, EarlyView.In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes +32 more
wiley +1 more source