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Results 81 to 90 of about 127,975,471 (298)

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

The categorisation of the Short Warwick Edinburgh Mental Wellbeing Scale scores: an exploration from an epidemiological perspective

Frontiers in Psychiatry
BackgroundThere 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

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

Estimating the Area under a Receiver Operating Characteristic Curve For Repeated Measures Design

Journal of Statistical Software, 2003
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
doaj +1 more source

Accuracy of logistic models and receiver operating characteristic curves [PDF]

The accuracy of prediction is a commonly studied topic in modern statistics. The performance of a predictor is becoming increasingly more important as real-life decisions axe made on the basis of prediction.
Corbett, Philip
core

Area under the ROC curve (AUC) for three validation sets.

, 2019
Area under the ROC curve (AUC) for three validation sets.
Lingzhi Wang (114519) +5 more
core +1 more source

The area under curve (AUC) of the ROC curve of various models in Tox21, ToxCast, MUV and HIV data sets.

, 2022
The area under curve (AUC) of the ROC curve of various models in Tox21, ToxCast, MUV and HIV data sets.
Xiaofei Sun (196958) +4 more
core +1 more source

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian +6 more
wiley +1 more source

Joint Statistical Inference for the Area under the ROC Curve and Youden Index under a Density Ratio Model

Mathematics
The receiver operating characteristic (ROC) curve is a valuable statistical tool in medical research. It assesses a biomarker’s ability to distinguish between diseased and healthy individuals.
Siyan Liu, Qinglong Tian, Yukun Liu, Pengfei Li +3 more
doaj +1 more source

Maximizing the Area under the ROC Curve Using Incremental Reduced Error Pruning

, 2005
The use of incremental reduced error pruning for maximizing the area under the ROC curve (AUC) instead of accuracy is ...
Henrik Boström, Boström, Henrik
core

roc curve
area under curve
area under the curve

humans
area under the curve auc
machine learning

auc
receiver operating characteristic roc
medicine