Results 31 to 40 of about 263,702 (262)
Receiver Operating Characteristic (ROC) Curves
Receiver operating characteristic (ROC) curves are used ubiquitously to evaluate covariates, markers, or features as potential predictors in binary problems. We distinguish raw ROC diagnostics and ROC curves, elucidate the special role of concavity in interpreting and modelling ROC curves, and establish an equivalence between ROC curves and cumulative ...
Gneiting, Tilmann, Vogel, Peter
openaire +2 more sources
Familiarity, recollection, and receiver-operating characteristic (ROC) curves in recognition memory [PDF]
The Atkinson-Shiffrin theory describes and explains some of the processes involved in storing and retrieving information in human memory. Here we examine predictions of related models for search and decision processes in recognizing information in long-term memory.
Juola, James F. +4 more
openaire +3 more sources
Background: Psychiatrists use different scales to evaluate post-stroke depression; however, some concerns have raised about their low specificity. Objectives: This study aimed to assess the validity and reliability of the Persian version of the Post ...
Somayeh Shokrgozar +5 more
doaj
Acceptance sampling for attributes via hypothesis testing and the hypergeometric distribution
This paper questions some aspects of attribute acceptance sampling in light of the original concepts of hypothesis testing from Neyman and Pearson (NP).
Robert Wayne Samohyl
doaj +1 more source
ROCS: receiver operating characteristic surface for class-skewed high-throughput data. [PDF]
The receiver operating characteristic (ROC) curve is an important tool to gauge the performance of classifiers. In certain situations of high-throughput data analysis, the data is heavily class-skewed, i.e.
Tianwei Yu
doaj +1 more source
A Linear Regression Framework for the Receiver Operating Characteristic(ROC) Curve Analysis [PDF]
The receiver operating characteristic (ROC) curve has been a popular statistical tool for characterizing the discriminating power of a classifier, such as a biomarker or an imaging modality for disease screening or diagnosis. It has been recognized that the accuracy of a given procedure may depend on some underlying factors, such as subject's ...
Zhang, Zheng, Huang, Ying
openaire +3 more sources
Combining biomarkers and their statistics is used to increase the prediction performance of a diagnosis, but no gold standard method exists. We introduced and evaluated an approach using linear combinations of summary-based statistics tested in logistic ...
Ilie-Andrei CONDURACHE +1 more
doaj
Many patients with urothelial cancer do not benefit from treatment with pembrolizumab, while at risk of severe side effects. Changes in the levels of circulating tumor DNA early during treatment, measured by a simple and affordable assay that can be easily implemented in the clinic, can be used as a prognostic tool to identify these patients.
Youssra Salhi +14 more
wiley +1 more source
Liquid biopsy‐based diagnostic evaluation of hypermethylated CpG sites for ovarian cancer diagnosis
This schematic outlines the workflow from biomarker identification to duplex MethyLight assay validation for epithelial ovarian cancer diagnosis using cfDNA‐based liquid biopsy. Initial screening of hypermethylated CpG candidates (cg02957270, cg10061138 cg00480298, COL2A1) was performed in tissue using ARMS‐PCR, COBRA, qPCR and image analysis. Selected
Deepa Bisht +3 more
wiley +1 more source
Systemic dysregulation of apolipoproteins in amyotrophic lateral sclerosis serum
Amyotrophic lateral sclerosis (ALS) is a fatal disease that damages motor neurons. This study found that people with ALS show significant changes in blood fats and the proteins that carry them. Several apolipoproteins were higher, lipid balances were altered, and normal protein–lipid relationships were disrupted.
Finula I. Isik +6 more
wiley +1 more source

