Results 121 to 130 of about 4,109,960 (295)

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah   +7 more
wiley   +1 more source

SRM Special Issue: Inference from Non Probability Samples

open access: yesSurvey Research Methods, 2017
Survey Research Methods, Vol 11, No 1 (2017)
openaire   +2 more sources

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein   +7 more
wiley   +1 more source

Graph Laplacians and their convergence on random neighborhood graphs

open access: yes, 2007
Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the submanifold.
Audibert, Jean-Yves   +2 more
core  

Use of Symptomatic Drug Treatment for Fatigue in Multiple Sclerosis and Patterns of Work Loss

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To describe the use of central stimulants and amantadine for fatigue in MS and evaluate a potential association with reduced work loss in people with MS. Methods We conducted a nationwide, matched, register‐based cohort study in Sweden (2006 to 2023) using national registers with prospective data collection.
Simon Englund   +3 more
wiley   +1 more source

Optimal futility stopping boundaries for binary endpoints

open access: yesBMC Medical Research Methodology
Background Group sequential designs incorporating the option to stop for futility at the time point of an interim analysis can save time and resources.
Michaela Maria Freitag   +2 more
doaj   +1 more source

Sample Attrition in the Presence of Population Attrition [PDF]

open access: yes
This paper develops a method that accounts for non-ignorable sample attrition in the presence of population attrition for use with a non-representative panel sample.
Seik Kim
core  

Hospital Readmission After Traumatic Brain Injury Hospitalization in Community‐Dwelling Older Adults

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the risk of hospital readmission after an index hospitalization for TBI in older adults. Methods Using data from the Atherosclerosis Risk in Communities (ARIC) study, we used propensity score matching of individuals with an index TBI‐related hospitalization to individuals with (1) non‐TBI hospitalizations (primary analysis)
Rachel Thomas   +7 more
wiley   +1 more source

Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky   +8 more
wiley   +1 more source

Refereeing the referees: evaluating two-sample tests for validating generators in precision sciences

open access: yesMachine Learning: Science and Technology
We propose a robust methodology to evaluate the performance and computational efficiency of non-parametric two-sample tests, specifically designed for high-dimensional generative models in scientific applications such as in particle physics.
Samuele Grossi   +2 more
doaj   +1 more source

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