Results 101 to 110 of about 2,068,010 (305)

Random Survival Forests per la stratificazione del rischio in pazienti affetti da Sclerosi Laterale Amiotrofica [PDF]

, 2022
A partire da dati clinici e demografici estratti dal database PRO-ACT (Amyotrophic Lateral Sclerosis Clinical Trial), si implementa l'algoritmo Random Survival Forests per ottenere una predizione del rischio di morte, a partire dalle variabili registrate
Tavazzi, Erica
core  

Analyzing Household Expenditures with Generalized Random Forests

Cauchy: Jurnal Matematika Murni dan Aplikasi
This 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, Khairil Anwar Notodiputro, Kusman Sadik   +2 more
doaj   +1 more source

Calibrating Random Forests

2008 Seventh International Conference on Machine Learning and Applications, 2008
When using the output of classifiers to calculate the expected utility of different alternatives in decision situations, the correctness of predicted class probabilities may be of crucial importance. However, even very accurate classifiers may output class probabilities of rather poor quality.
openaire   +4 more sources

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, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Modern Management of Asymptomatic Carotid Stenosis: A Meta‐Analysis of CREST‐2, SPACE‐2, and ECST‐2

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Recent randomized trials (CREST‐2, SPACE‐2, and ECST‐2) have compared carotid revascularization (carotid endarterectomy [CEA] or carotid artery stenting [CAS]) plus contemporary medical therapy (CMT) versus CMT alone in asymptomatic carotid stenosis.
Aasim Ali, Waqar Ahmed Cheema, Fiza Nisar, Muhammad Shamoon, Sameen Sarfaraz, Ahmad Butt, Muhammad Abdullah Ali, Armaghana Abdullah, Muhammad Asad Shabbir, Muhammad Talha, Hammad Azam, Aimen Anwaar Pannun, Usama Saleem, Anousha Tanveer, Mukesh Sharma   +14 more
wiley   +1 more source

Classification of PolSAR Images by Stacked Random Forests

ISPRS International Journal of Geo-Information, 2018
This paper proposes the use of Stacked Random Forests (SRF) for the classification of Polarimetric Synthetic Aperture Radar images. SRF apply several Random Forest instances in a sequence where each individual uses the class estimate of its predecessor ...
Ronny Hänsch, Olaf Hellwich
doaj   +1 more source

Reserves, Injury Severity, and Outcomes in Traumatic Brain Injury: A CENTER‐TBI Observational Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Reserve refers to the brain's ability to maintain function after an injury and strongly relates to traumatic brain injury (TBI) outcomes. This study examined (1) whether associations between pre‐injury reserve proxies and outcomes differed across injury severity categories, and (2) whether the impact of injury severity varied across ...
Natascha Ekdahl, Marika C. Möller, Lindsay Wilson, Anne Vik, Toril Skandsen, Jonas Stenberg, CENTER‐TBI participants and investigators   +6 more
wiley   +1 more source

Random convolution ensembles [PDF]

, 2007
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is generated and applied to all of the images in the labeled training set. The
Mayo, Michael
core   +1 more source

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Random Forests for Multiclass Classification: Random

, 2008
—Several supervised learning algorithms are suited to classify instances into a multiclass value space. MultiNomial Logit (MNL) is recognized as a robust classifier and is commonly applied within the CRM (Customer Relationship Management) domain ...
Multinomial Logit, Random Multinomial Logit   +1 more
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