Colon cancer diagnosis and staging classification based on machine learning and bioinformatics analysis

Human serum mid-infrared spectroscopy combined with machine learning algorithms for rapid detection of gliomas

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Determination of a six-gene prognostic model for cervical cancer based on WGCNA combined with LASSO and Cox-PH analysis

(2021) Shiyan Li et al.   World Journal of Surgical Oncology

Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer

(2021) Neha Shree Maurya et al.   Scientific Reports

Colorectal cancer statistics, 2020

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Deep learning to find colorectal polyps in colonoscopy: A systematic literature review

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Identification of co-expression modules and potential biomarkers of breast cancer by WGCNA

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Rapid, non-invasive screening of keratitis based on Raman spectroscopy combined with multivariate statistical analysis

(2020) Xiaodong Xie et al.   Photodiagnosis and Photodynamic Therapy

Early lung cancer diagnostic biomarker discovery by machine learning methods

(2020) Ying Xie et al.   Translational Oncology

Fecal occult blood test in colorectal cancer screening

(2019) Jing Nan Li et al.   Journal of Digestive Diseases

Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis

(2019) Yu Di et al.   HEREDITAS

Presenting symptoms of cancer and stage at diagnosis: evidence from a cross-sectional, population-based study

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Application of Weighted Gene Co-expression Network Analysis for Data from Paired Design

(2018) Jianqiang Li et al.   Scientific Reports

Liquid Biopsy in Colorectal Cancer-Current Status and Potential Clinical Applications

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Decision tree classifiers for evidential attribute values and class labels

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Machine learning applications in cancer prognosis and prediction

(2015) Konstantina Kourou et al.   Computational and Structural Biotechnology Journal

Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types

(2014) Yang Yang et al.   Nature Communications

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

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Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients

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