2020
DOI: 10.1590/1677-5449.200186
|View full text |Cite
|
Sign up to set email alerts
|

Aplicações da curva ROC em estudos clínicos e experimentais

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

1
36
0
8

Year Published

2021
2021
2024
2024

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 59 publications
(65 citation statements)
references
References 30 publications
1
36
0
8
Order By: Relevance
“…ROC analysis depicted the comparisons of cut-off values with respect to sensitivity and specificity of K. Similarly, the AUC explained the overall performance of diagnostic test. AUC = 0.5 is not good and non-informative for the diagnostic test, AUC = between 0.5 and 0.7 depicts the less accurate value for the diagnostic test, AUC = between 0.7 and 0.9 indicates the moderately accurate, AUC = between 0.9 and 1 indicates the highly accurate value for the diagnostic test while AUC = 1.000 indicates the perfect test, and the diagnostic test is perfect for the diagnosis of positive and negative sera [ 45 ]. Subsequently, AUC = 1.000 of K indicated that this test was perfect test for the diagnosis of positive and negative sera of toxoplasmosis.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…ROC analysis depicted the comparisons of cut-off values with respect to sensitivity and specificity of K. Similarly, the AUC explained the overall performance of diagnostic test. AUC = 0.5 is not good and non-informative for the diagnostic test, AUC = between 0.5 and 0.7 depicts the less accurate value for the diagnostic test, AUC = between 0.7 and 0.9 indicates the moderately accurate, AUC = between 0.9 and 1 indicates the highly accurate value for the diagnostic test while AUC = 1.000 indicates the perfect test, and the diagnostic test is perfect for the diagnosis of positive and negative sera [ 45 ]. Subsequently, AUC = 1.000 of K indicated that this test was perfect test for the diagnosis of positive and negative sera of toxoplasmosis.…”
Section: Resultsmentioning
confidence: 99%
“…The ROC is used to find out the cut-off value of ELISA for the detection of positive and negative sera for anti- T. gondii antibodies. It is also used to determine the efficacy of diagnostic kits for detection of antibodies [ 44 , 45 ]. In the study of K development, the cut-off value was 0.398, AUC for K was 1.000, and it was highly significant ( p < 0.001).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Para recursos de mensuração quantitativa, a análise da curva ROC representa a ferramenta mais adequada para o estabelecimento desses parâmetros. 20…”
Section: Materiais E Métodounclassified
“…Contudo, ao passo que se emprega a estatística para concluir quanto à diferença entre amostras, a maior variabilidade das medidas e a modesta diferença entre grupos comprometem o poder analítico (erro tipo II). Esse detalhe exige uma cuidadosa interpretação do p-valor (significância estatística) e da dimensão do efeito na inferência resultante de estudos de comparação entre grupos, apesar desses conceitos se aplicarem também a análises de correlação, concordância, sobrevivência, testes diagnósticos, entre outros [1][2][3][4][5] .…”
unclassified