ArticleOncology letters2026
Predictive performance of image processing techniques in the diagnosis of bone metastasis: A meta-analysis of a confusion matrix.
Article in Oncology letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Bone metastasis, a common cause of disability, markedly affects prognosis and life expectancy, and is usually diagnosed through radiographic imaging. An early and accurate diagnosis of bone metastasis is critical in order to optimize therapeutic strategies and palliative care. Computer-based image processing techniques have proved promising to improve diagnostic efficiency. The present systematic review and meta-analysis aimed to evaluate the efficacy of the diagnostic performance metrics of computational image processing techniques in patients with lung cancer and bone metastasis. Following the Preferred Reporting Items for Systematic reviews and Meta-analysis guidelines, a comprehensive literature search was conducted across different databases between January 2010 and December 2024. Studies assessing computational image-processing techniques in patients with lung cancer and bone metastasis were included. Confusion matrix parameters were extracted and the bivariate Reitsma model was applied to estimate the pooled diagnostic performance. Heterogeneity and inconsistency (variance of components and I
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