{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T20:52:34Z","timestamp":1773262354334,"version":"3.50.1"},"reference-count":37,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers in Biology and Medicine"],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1016\/j.compbiomed.2022.105409","type":"journal-article","created":{"date-parts":[[2022,3,19]],"date-time":"2022-03-19T11:35:39Z","timestamp":1647689739000},"page":"105409","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":160,"special_numbering":"C","title":["Colon cancer diagnosis and staging classification based on machine learning and bioinformatics analysis"],"prefix":"10.1016","volume":"145","author":[{"given":"Ying","family":"Su","sequence":"first","affiliation":[]},{"given":"Xuecong","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Rui","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Wenjia","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Cheng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Chen","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Dongfang","family":"Jia","sequence":"additional","affiliation":[]},{"given":"Hongtao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xiaoyi","family":"Lv","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.compbiomed.2022.105409_bib1","first-page":"145","article-title":"Colorectal cancer statistics, 2020","volume":"70","author":"Siegel","year":"2020","journal-title":"CA A Cancer J. Clin."},{"key":"10.1016\/j.compbiomed.2022.105409_bib2","unstructured":"Statistics | Cancer.Net. [(accessed on 27 November 2021)]; Available online: https:\/\/www.cancer.net\/cancer-types\/colorectal-cancer\/statistics."},{"issue":"2","key":"10.1016\/j.compbiomed.2022.105409_bib3","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1111\/1751-2980.12712","article-title":"Fecal occult blood test in colorectal caPhotodiagnosis Photodyn. Ther.ncer screening","volume":"20","author":"Li","year":"2019","journal-title":"Journal of digestive diseases"},{"issue":"3313","key":"10.1016\/j.compbiomed.2022.105409_bib4","article-title":"Scope of artificial intelligence in screening and diagnosis of colorectal cancer[J]","volume":"9","author":"Goyal","year":"2020","journal-title":"J. Clin. Med."},{"issue":"6","key":"10.1016\/j.compbiomed.2022.105409_bib5","first-page":"289","article-title":"Epigenetic modification of gene expression in colorectal carcinogenesis","volume":"11","author":"Krakowczyk","year":"2007","journal-title":"Wsp\u00f3lczesna Onkol."},{"key":"10.1016\/j.compbiomed.2022.105409_bib6","series-title":"Principles of Molecular Oncology","first-page":"233","article-title":"Circulating tumor markers","author":"Horwich","year":"2004"},{"key":"10.1016\/j.compbiomed.2022.105409_bib7","unstructured":"Staged | Cancer.Net. [(accessed on 27 November 2021)]; Available online:https:\/\/www.cancer.org\/cancer\/colon-rectal-cancer\/detection-diagnosis-staging\/staged."},{"key":"10.1016\/j.compbiomed.2022.105409_bib8","unstructured":"Stage, T., Stage, N., & Stage, M. Carcinoma in Situ Corresponds to the TNM Classification. Laryngeal Cancer: Stages. M-distant metastases."},{"key":"10.1016\/j.compbiomed.2022.105409_bib9","unstructured":"Stages of Cancer | Cancer.Net. [(accessed on 27 November 2021)]; Availableonline: https:\/\/www.cancer.net\/navigating-cancer-care\/diagnosing-cancer\/stages-cancer."},{"key":"10.1016\/j.compbiomed.2022.105409_bib10","unstructured":"Cancer Survival Rates. [(accessed on 27 November 2021)]; Available online: https:\/\/cancersurvivalrates.com\/?type=colon&role=patient."},{"key":"10.1016\/j.compbiomed.2022.105409_bib11","doi-asserted-by":"crossref","first-page":"101923","DOI":"10.1016\/j.artmed.2020.101923","article-title":"Deep learning to find colorectal polyps in colonoscopy: a systematic literature review","author":"S\u00e1nchez-Peralta","year":"2020","journal-title":"Artif. Intell. Med."},{"key":"10.1016\/j.compbiomed.2022.105409_bib12","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.csbj.2014.11.005","article-title":"Machine learning applications in cancer prognosis and prediction","volume":"13","author":"Kourou","year":"2015","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"10.1016\/j.compbiomed.2022.105409_bib13","series-title":"The Nature of Statistical Learning Theory","author":"Vapnik","year":"1999"},{"key":"10.1016\/j.compbiomed.2022.105409_bib14","volume":"vol. 204","author":"Shawe-Taylor","year":"2000"},{"key":"10.1016\/j.compbiomed.2022.105409_bib15","series-title":"Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines","author":"Platt","year":"1998"},{"issue":"1","key":"10.1016\/j.compbiomed.2022.105409_bib16","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"10.1016\/j.compbiomed.2022.105409_bib17","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.fss.2018.11.006","article-title":"Decision tree classifiers for evidential attribute values and class labels","volume":"366","author":"Trabelsi","year":"2019","journal-title":"Fuzzy Set Syst."},{"key":"10.1016\/j.compbiomed.2022.105409_bib18","series-title":"Encyclopedia of Bioinformatics and Computational Biology","first-page":"374","article-title":"Decision trees and random forests","author":"Fratello","year":"2019"},{"key":"10.1016\/j.compbiomed.2022.105409_bib19","doi-asserted-by":"crossref","first-page":"101932","DOI":"10.1016\/j.pdpdt.2020.101932","article-title":"Rapid, non-invasive screening of keratitis based on Raman spectroscopy combined with multivariate statistical analysis","volume":"31","author":"Xie","year":"2020","journal-title":"Photodiagnosis Photodyn. Ther."},{"key":"10.1016\/j.compbiomed.2022.105409_bib20","doi-asserted-by":"crossref","first-page":"102308","DOI":"10.1016\/j.pdpdt.2021.102308","article-title":"Human serum mid-infrared spectroscopy combined with machine learning algorithms for rapid detection of gliomas","volume":"35","author":"Chen","year":"2021","journal-title":"Photodiagn. Photodynamic Ther."},{"key":"10.1016\/j.compbiomed.2022.105409_bib21","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s13721-020-00249-4","article-title":"A novel approach to identify subtype-specific network biomarkers of breast cancer survivability","volume":"9","author":"Jubair","year":"2020","journal-title":"Netw Model Anal. Health Inform. Bioinfo."},{"key":"10.1016\/j.compbiomed.2022.105409_bib22","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1186\/s12957-021-02384-2","article-title":"Determination of a six-gene prognostic model for cervical cancer based on WGCNA combined with LASSO and Cox-PH analysis","volume":"19","author":"Li","year":"2021","journal-title":"World J. Surg. Oncol."},{"issue":"1","key":"10.1016\/j.compbiomed.2022.105409_bib23","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1038\/s41598-017-18705-z","article-title":"Application of weighted gene Co-expression network analysis for data from paired design","volume":"8","author":"Li","year":"2018","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compbiomed.2022.105409_bib24","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1186\/1471-2164-10-405","article-title":"Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients","volume":"10","author":"Saris","year":"2009","journal-title":"BMC Genom."},{"key":"10.1016\/j.compbiomed.2022.105409_bib25","doi-asserted-by":"crossref","first-page":"3231","DOI":"10.1038\/ncomms4231","article-title":"Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types","volume":"5","author":"Yang","year":"2014","journal-title":"Nat. Commun."},{"key":"10.1016\/j.compbiomed.2022.105409_bib26","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s41065-019-0083-y","article-title":"Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis","volume":"156","author":"Di","year":"2019","journal-title":"Hereditas"},{"key":"10.1016\/j.compbiomed.2022.105409_bib27","doi-asserted-by":"crossref","first-page":"144757","DOI":"10.1016\/j.gene.2020.144757","article-title":"Identification of co-expression modules and potential biomarkers of breast cancer by WGCNA","volume":"750","author":"Jia","year":"2020","journal-title":"Gene"},{"key":"10.1016\/j.compbiomed.2022.105409_bib28","article-title":"Simultaneous feature selection and clustering based on square root optimization[J]","author":"Jiang","year":"2020","journal-title":"Eur. J. Oper. Res."},{"key":"10.1016\/j.compbiomed.2022.105409_bib29","series-title":"2021 IEEE International Conference on Bioinformatics and Biomedicine","first-page":"2301","article-title":"LASSO-based feature selection for improved microbial and microbiome classification","author":"Queen","year":"2021"},{"key":"10.1016\/j.compbiomed.2022.105409_bib30","doi-asserted-by":"crossref","first-page":"14304","DOI":"10.1038\/s41598-021-92692-0","article-title":"Transcriptome profiling by combined machine learning and statistical R analysis identifies TMEM236 as a potential novel diagnostic biomarker for colorectal cancer","volume":"11","author":"Maurya","year":"2021","journal-title":"Sci. Rep."},{"key":"10.1016\/j.compbiomed.2022.105409_bib31","unstructured":"Stages of Cancer | Webmd.Com. [(accessed on 5 December 2021)]; Available online: https:\/\/www.webmd.com\/cancer\/cancer-stages."},{"issue":"1","key":"10.1016\/j.compbiomed.2022.105409_bib32","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1093\/bioinformatics\/btp616","article-title":"edgeR: a Bioconductor package for differential expression analysis of digital gene expression data","volume":"26","author":"Robinson","year":"2010","journal-title":"Bioinformatics"},{"key":"10.1016\/j.compbiomed.2022.105409_bib33","doi-asserted-by":"crossref","DOI":"10.2202\/1544-6115.1027","article-title":"Linear models and empirical bayes methods for assessing differential expression in microarray experiments","volume":"3","author":"Smyth","year":"2004","journal-title":"Stat. Appl. Genet. Mol. Biol."},{"issue":"1","key":"10.1016\/j.compbiomed.2022.105409_bib34","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/S1470-2045(19)30595-9","article-title":"Presenting symptoms of cancer and stage at diagnosis: evidence from a cross-sectional, population-based study","volume":"21","author":"Koo","year":"2020","journal-title":"Lancet Oncol"},{"issue":"6","key":"10.1016\/j.compbiomed.2022.105409_bib35","doi-asserted-by":"crossref","first-page":"300","DOI":"10.3390\/mi9060300","article-title":"Liquid biopsy in colorectal cancer-current status and potential clinical applications","volume":"9","author":"Norcic","year":"2018","journal-title":"Micromachines"},{"issue":"1","key":"10.1016\/j.compbiomed.2022.105409_bib36","doi-asserted-by":"crossref","first-page":"100907","DOI":"10.1016\/j.tranon.2020.100907","article-title":"Early lung cancer diagnostic biomarker discovery by machine learning methods[J]","volume":"14","author":"Xie","year":"2021","journal-title":"Translational Oncol."},{"key":"10.1016\/j.compbiomed.2022.105409_bib37","series-title":"Study of Growth Factor-Induced Epithelial-Mesenchymal Transition in Human Colon Cancer Cells [D]","author":"Hong","year":"2011"}],"container-title":["Computers in Biology and Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0010482522002013?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0010482522002013?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,14]],"date-time":"2025-09-14T19:42:52Z","timestamp":1757878972000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0010482522002013"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6]]},"references-count":37,"alternative-id":["S0010482522002013"],"URL":"https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105409","relation":{},"ISSN":["0010-4825"],"issn-type":[{"value":"0010-4825","type":"print"}],"subject":[],"published":{"date-parts":[[2022,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Colon cancer diagnosis and staging classification based on machine learning and bioinformatics analysis","name":"articletitle","label":"Article Title"},{"value":"Computers in Biology and Medicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.compbiomed.2022.105409","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"105409"}}