2020
DOI: 10.1080/15321819.2020.1779740
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Classifying multiple lung cancers using morphological features: a meta-analysis

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Cited by 3 publications
(2 citation statements)
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“…The heterogeneity was calculated using inconsistency indexes (I 2 ). In consistence with criteria used by previous meta-analyses, an I 2 > 50% was determined as an indicator of substantial heterogeneity between studies [11,12]. If the heterogeneity was significant, a random-effects model was used.…”
Section: Synthesis Methodsmentioning
confidence: 99%
“…The heterogeneity was calculated using inconsistency indexes (I 2 ). In consistence with criteria used by previous meta-analyses, an I 2 > 50% was determined as an indicator of substantial heterogeneity between studies [11,12]. If the heterogeneity was significant, a random-effects model was used.…”
Section: Synthesis Methodsmentioning
confidence: 99%
“…Meta-analysis expands the sample size, improves the efficiency of tests, reduces random errors, and improves the accuracy of evaluation effectiveness. Through a meta-analysis, Mlika et al (44) found that morphological features may be helpful for the diagnosis of multiple lung cancer, especially when dealing with surgical specimens. Pooled sensitivity (PSEN) was estimated to be 65%, pooled specificity (PSPE) 49%, and AUC 0.63.…”
Section: Discussionmentioning
confidence: 99%