Results 91 to 100 of about 338,729 (282)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) have demonstrated significant weight‐reducing effects and may offer benefits in idiopathic intracranial hypertension (IIH); however, recent concerns about the risk of non‐arteritic anterior ischemic optic neuropathy (NAION) have emerged.
Faisal A. Al‐Harbi +9 more
wiley +1 more source
On the overestimation of random forest's out-of-bag error. [PDF]
PLoS ONE, 2018 The ensemble method random forests has become a popular classification tool in bioinformatics and related fields. The out-of-bag error is an error estimation technique often used to evaluate the accuracy of a random forest and to select appropriate ...
Silke Janitza, Roman Hornung
doaj +1 more source
Correlation and variable importance in random forests
, 2016 This paper is about variable selection with the random forests algorithm in presence of correlated predictors. In high-dimensional regression or classification frameworks, variable selection is a difficult task, that becomes even more challenging in the ...
Gregorutti, Baptiste +2 more
core +2 more sources
CoRRWe propose a principled method for autoencoding with random forests. Our strategy builds on foundational results from nonparametric statistics and spectral graph theory to learn a low-dimensional embedding of the model that optimally represents relationships in the data. We provide exact and approximate solutions to the decoding problem via constrained
Binh Duc Vu +3 more
openaire +2 more sources
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
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
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
Arthritis Care &Research, EarlyView.Objective Relapsing polychondritis (RP) is a rare disease defined by recurrent cartilaginous inflammation. Anti–collagen II (Col2) antibodies have been proposed as a diagnostic biomarker for RP, but their performance characteristics are not well defined.
Karyssa Stonick +6 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Objective We examined whether 18 months of strength training in individuals with knee varus alignment and medial tibiofemoral osteoarthritis (OA) reduced knee joint loads during walking compared to an attention control group. Methods This study was a secondary analysis of a randomized clinical trial that compared the effects of strength training to a ...
Stephen P. Messier +12 more
wiley +1 more source
Analyzing Household Expenditures with Generalized Random Forests
Cauchy: Jurnal Matematika Murni dan AplikasiThis study investigates the performance of Generalized Random Forest (GRF), which has been known to be useful in understanding heterogeneous treatment effects (HTE) and non-linear relationships in high-dimensional data.
Eriski Isnanda +2 more
doaj +1 more source