Results 91 to 100 of about 2,068,010 (305)
Bioinformatics, 2008 Abstract Although the random forest classification procedure works well in datasets with many features, when the number of features is huge and the percentage of truly informative features is small, such as with DNA microarray data, its performance tends to decline significantly.
Dhammika Amaratunga +2 more
openaire +3 more sources
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Neurochemical levels measured by brain MR spectroscopy (MRS) have been proposed as endpoints for clinical trials in early‐stage spinocerebellar ataxia (SCA) trials. We tested their trial‐readiness by quantifying neurochemicals in three affected brain regions in early‐stage cohorts of SCA2 and SCA3, examining their reproducibility in ...
James M. Joers +19 more
wiley +1 more source
Random forests estocástico [PDF]
, 2012 In the Data Mining area experiments have been carried out using Ensemble Classifiers. We experimented Random Forests to evaluate the performance when randomness is applied.
Gómez, Silvio Normey
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate which baseline clinical and imaging characteristics best predict TSPO‐PET‐measurable reduction in glial activation following treatment of multiple sclerosis (MS), to utilize this information for designing more efficient biomarker‐based clinical trials targeting glial activation.
Marlene T. Morch +5 more
wiley +1 more source
, 2006 Exhaustive search in relational learning is generally infeasible, therefore some form of heuristic search is usually employed, such as in FOIL[1]. On the other hand, so-called stochastic discrimination provides a framework for combining arbitrary numbers
Pfahringer, Bernhard, Anderson, Grant
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The Macroeconomy as a Random Forest [PDF]
SSRN Electronic Journal, 2020 SummaryI develop the macroeconomic random forest (MRF), an algorithm adapting the canonical machine learning (ML) tool, to flexibly model evolving parameters in a linear macro equation. Its main output, generalized time‐varying parameters (GTVPs), is a versatile device nesting many popular nonlinearities (threshold/switching, smooth transition, and ...
openaire +2 more sources
Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu +7 more
wiley +1 more source
Biodiversity shapes tree species aggregations in tropical forests [PDF]
, 2008 Spatial patterns of conspecific trees are considered as the consequences of biological interactions and environmental influences. They also reflect species interactions in plant communities.
Chang-Fu Hsieh +2 more
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