Prognostic assessment capability of a five-gene signature in pancreatic cancer: a machine learning based-study - BMC Gastroenterology

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Prognostic assessment capability of a five-gene signature in pancreatic cancer: a machine learning based-study - BMC Gastroenterology
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A study published in BMCGastroEnterol discusses a novel 5-gene signature as a prognostic assessment model for pancreatic cancer patients.

), the expression data was normalized by RMA. The expression levels of TCGA-PAAD and GTEx were rescaled using FPKM as the unit of measure for subsequent analyses. Differentially expressed genes was identified using Limma package in R. The cut-off value was set to |logFC|> 1 andA, there are 178 tumor samples and 4 normal samples in TCGA-PAAD dataset.

167 normal samples in GTEx-PAAD dataset, 45 tumor samples and 45 normal samples in GSE28735, 69 tumor samples and 61 normal samples in GSE62452. The TCGA-PAAD and GTEx-PAAD are RNA-seq data, the expression data in them were normalized by FPKM. GSE28735 and GSE62452 share the same platform which ID is GPL6244. The expression data in the array chips was normalized into RAM. Limma R package was used for differential expression analysis.

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How Merseyside health staff are cutting down NHS wait lists with artificial intelligenceHow Merseyside health staff are cutting down NHS wait lists with artificial intelligence🩺 Clinical leaders in Cheshire and Merseyside have been using machine learning to help surgeons prioritise waiting lists, reducing bureaucracy and freeing up consultants’ time to help clear the backlog PMGallagher1 reports:
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