Results 81 to 90 of about 24,246,868 (339)
Characterizing Cutaneous α‐Synuclein Deposition and Seeding Activity in Parkinson's Disease Subtypes
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Cutaneous phosphorylated α‐synuclein (p‐syn) and α‐synuclein seeding activity are promising biomarkers for Parkinson's disease (PD), but their clinical value remains uncertain due to disease heterogeneity. This study evaluates these two biomarkers in PD patients to inform phenotype‐specific diagnosis and disease severity assessment ...
Yuting Jin +8 more
wiley +1 more source
Estimating the Area under a Receiver Operating Characteristic Curve For Repeated Measures Design [PDF]
The receiver operating characteristic (ROC) curve is widely used for diagnosing as well as for judging the discrimination ability of different statistical models.
Honghu Liu, Tongtong Wu
core
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
An Improved Method for Bandwidth Selection when Estimating ROC Curves [PDF]
The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups.
Peter Hall, Rob J. Hyndman
core
Receiver operating characteristic (ROC) curve.
, 2015 An example of Receiver operating characteristic (ROC) analysis for the prediction of ‘true segregating SNVs’ in the HY population using the allele frequencies in the exome capture experiment at a MAF threshold of 0.15.
Elena Pomari (803054) +4 more
core +1 more source
Receiver operating characteristic (ROC) curves of the different models.
, 2023 Receiver operating characteristic (ROC) curves of the different models.
Roderick P. Venekamp (10259098) +8 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
Frontiers in PsychiatryBackgroundThere has been a notable increase in the utilisation of SWEMWBS as a measure of mental well-being globally. To enhance its interpretability for both healthcare professionals and laypeople, categorising SWEMWBS scores is considered beneficial ...
Lawrence T. Lam +3 more
doaj +1 more source
Receiver-operating characteristic (ROC) curves (total study cohort) for LINKI algorithms.
, 2016 Receiver-operating characteristic (ROC) curves (total study cohort) for LINKI algorithms.
Byron Lykiardopoulos (3391277) +7 more
core +1 more source
Do unbalanced data have a negative effect on LDA? [PDF]
, 2008 For two-class discrimination, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] claimed that, when covariance matrices of the two classes were unequal, a (class ...
Titterington, D.M., Xue, J.H.
core +1 more source