Results 101 to 110 of about 17,286,028 (305)
Hyperparameters of type-1 radiomics model using random forest classifier.
, 2023 Hyperparameters of type-1 radiomics model using random forest classifier.
Seung-Han Shin (1416379) +7 more
core +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 Forest estimation of the ordered choice model
Empirical EconomicsAbstract In this paper we develop a new machine learning estimator for ordered choice models based on the Random Forest. The proposed Ordered Forest flexibly estimates the conditional choice probabilities while taking the ordering information explicitly into account. In addition to common machine learning estimators, it enables the estimation
Lechner, Michael, Okasa, Gabriel
openaire +4 more sources
Predicted incidence against observed HFMD incidence using Random Forest model.
, 2021 Predicted incidence against observed HFMD incidence using Random Forest model.
Jun Xu (45543) +2 more
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
SensorsAs one of the main external factors affecting the fire extinguishing accuracy of sprinkler systems, it is necessary to analyze and study random wind. However, in practical applications, there is little research on the impact of random wind on sprinkler ...
Hengyu Cheng +4 more
doaj +1 more source
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
, 2013 Extracts from the R script that THP used for building the random forest model. The number of trees (NT) and the number of variables tried at each split (MT) are obtained as described in the text.
Claus Holst (37670) +4 more
core +1 more source
Comparison of the proposed model with SVM, KNN, Random Forest.
, 2023 Comparison of the proposed model with SVM, KNN, Random Forest.
Wondmagegn Taye (13267979) +2 more
core +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source