Results 111 to 120 of about 3,628,827 (305)
On Boundary Correction in Kernel Estimation of ROC Curves
Austrian Journal of Statistics, 2016 The Receiver Operating Characteristic (ROC) curve is a statistical tool for evaluating the accuracy of diagnostics tests. The empirical ROC curve (which is a step function) is the most commonly used non-parametric estimator for the ROC curve.
Jan Koláček, Rohana J. Karunamuni
doaj +1 more source
nonbinROC: Software for Evaluating Diagnostic Accuracies with Non-Binary Gold Standards [PDF]
ROC analysis is a standard method for estimating and comparing diagnostic tests' accuracies when the gold standard is binary. However, there are many situations when the gold standard is not binary.
Paul Nguyen
core
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To identify inflammatory analytes in cerebrospinal fluid (CSF) and plasma associated with cognitive decline in cognitively normal (CN) older adults at risk for Alzheimer's disease (AD). Methods In a longitudinal study of 118 CN older adults (65–80 years, 54% APOE ε4, 26% preclinical AD), 1331 CSF and 1501 plasma analytes were ...
Jagan A. Pillai +13 more
wiley +1 more source
PresenceAbsence: An R Package for Presence Absence Analysis [PDF]
The PresenceAbsence package for R provides a set of functions useful when evaluating the results of presence-absence analysis, for example, models of species distribution or the analysis of diagnostic tests.
Elizabeth A. Freeman, Gretchen Moisen
core
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong +10 more
wiley +1 more source
Beyond the ROC Curve: Activity Monitoring to Evaluate Deep Learning Models in Clinical Settings
Applied Medical InformaticsWe evaluated ‘VITALCARE-SEPS’, a deep learning model for sepsis prediction, using the activity monitoring operator characteristics curve with two different scoring algorithms.
Hyunwoo CHOO +5 more
doaj
Arthritis Care &Research, EarlyView.Objective The study aimed to identify symptom‐based predictors of dry eye disease (DED) signs in the Sjögren's International Collaborative Clinical Alliance (SICCA) cohort. Methods We performed a retrospective analysis examining 16 ocular symptoms (most graded 0–4) and artificial tear (AT) use (graded 0–3) as predictors of DED signs (abnormal ocular ...
Pragnya R. Donthineni +7 more
wiley +1 more source
Clinical, Histologic, and Serological Predictors of Renal Function Loss in Lupus Nephritis
Arthritis Care &Research, EarlyView.Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang +21 more
wiley +1 more source
Receiver operating characteristic (ROC) curve for fecal calprotectin.
, 2016 Receiver operating characteristic (ROC) curve for fecal calprotectin in prediction the presence of acute appendicitis. The area under the curve (AUC) was 0.869 (95% confidence interval (CI) CI 0.715–1.0), p = 0.009.
Hubert Zirngibl (3608042) +3 more
core +1 more source
Advanced Healthcare Materials, EarlyView.Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei +9 more
wiley +1 more source