Results 91 to 100 of about 17,286,028 (305)
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
Benefit Transfer over Time of Ecosystem Values: the Case of Forest Recreation [PDF]
We conduct a functional benefit transfer over 20 years of total willingness to pay based on car-borne forest recreation in 52 forests, using a mixed specification of a random utility model and geographic information systems to allow heterogeneous ...
Mette Termansen +2 more
core
Feature importance values for the child-only random forest model.
, 2023 Feature importance values for the child-only random forest model.
Carlos A. Camargo Jr (10218054) +6 more
core +1 more source
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
Random Forests Model Selection.
, 2016 Random Forests (RF) of tree classifiers are a popular ensemble method for classification. RF have shown to be effective in many different real world classification problems and nowadays are considered as one of the best learning algorithms in this context.
ORLANDI, ILENIA +2 more
openaire +3 more sources
Feature importance values for the child-adult random forest model.
, 2023 Feature importance values for the child-adult random forest model.
Carlos A. Camargo Jr (10218054) +6 more
core +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
Analisis Komparatif Model Random Forest dan XGBoost Berdasarkan Kinerja AUC Pada Fraud Detection
Techno.ComFraud detection menjadi salah satu tantangan penting dalam sistem informasi modern, khususnya pada transaksi finansial dan digital. Berbagai penelitian telah menunjukkan performa tinggi model Random Forest dan XGBoost, namun sebagian besar evaluasi masih
Muthiah As Saidah, Aggry Saputra
doaj +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
A New Forest Growing Stock Volume Estimation Model Based on AdaBoost and Random Forest Model
Forest growing stock volume is a crucial indicator for assessing forest resources. However, contemporary machine learning models used in estimating forest growing stock volume often exhibit fluctuating precision and are confined to specific tree species,
Weiheng Xu +4 more
core +1 more source