{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T08:55:58Z","timestamp":1781772958067,"version":"3.54.5"},"reference-count":72,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"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":["Computer Methods and Programs in Biomedicine"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.cmpb.2025.109211","type":"journal-article","created":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T16:56:24Z","timestamp":1767027384000},"page":"109211","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Machine learning-assisted prognosis of multiple myeloma side population cells via SRGs and OCLR stemness index"],"prefix":"10.1016","volume":"276","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6655-4508","authenticated-orcid":false,"given":"Xufei","family":"Xiang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiyi","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-1394-5373","authenticated-orcid":false,"given":"Jicong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0506-3448","authenticated-orcid":false,"given":"Zefang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6586-8406","authenticated-orcid":false,"given":"Yang","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"5","key":"10.1016\/j.cmpb.2025.109211_b1","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1001\/jama.2022.0003","article-title":"Diagnosis and management of multiple myeloma: a review","volume":"327","author":"Cowan","year":"2022","journal-title":"Jama"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b2","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1038\/nrclinonc.2014.200","article-title":"Current treatment landscape for relapsed and\/or refractory multiple myeloma","volume":"12","author":"Dimopoulos","year":"2015","journal-title":"Nat. Rev. Clin. Oncol."},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.canlet.2008.08.005","article-title":"Cancer stem cells in multiple myeloma","volume":"277","author":"Ghosh","year":"2009","journal-title":"Cancer Lett."},{"issue":"8","key":"10.1016\/j.cmpb.2025.109211_b4","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1016\/j.trecan.2024.06.002","article-title":"Targeting cancer stem cells in multiple myeloma","volume":"10","author":"Gunes","year":"2024","journal-title":"Trends Cancer"},{"issue":"4","key":"10.1016\/j.cmpb.2025.109211_b5","doi-asserted-by":"crossref","first-page":"1797","DOI":"10.1084\/jem.183.4.1797","article-title":"Isolation and functional properties of murine hematopoietic stem cells that are replicating in vivo","volume":"183","author":"Goodell","year":"1996","journal-title":"J. Exp. Med."},{"issue":"22","key":"10.1016\/j.cmpb.2025.109211_b6","doi-asserted-by":"crossref","first-page":"6155","DOI":"10.1158\/1078-0432.CCR-12-0531","article-title":"Stemness of B-cell progenitors in multiple myeloma bone marrow","volume":"18","author":"Boucher","year":"2012","journal-title":"Clin. Cancer Res."},{"issue":"8","key":"10.1016\/j.cmpb.2025.109211_b7","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1182\/blood-2013-02-482919","article-title":"RARalpha2 expression confers myeloma stem cell features","volume":"122","author":"Yang","year":"2013","journal-title":"Blood"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.canlet.2008.03.048","article-title":"Side population cells in human cancers","volume":"268","author":"Wu","year":"2008","journal-title":"Cancer Lett."},{"issue":"5","key":"10.1016\/j.cmpb.2025.109211_b9","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1002\/ijc.29078","article-title":"Dynamic balance of multiple myeloma clonogenic side population cell percentages controlled by environmental conditions","volume":"136","author":"Wen","year":"2015","journal-title":"Int. J. Cancer"},{"issue":"2","key":"10.1016\/j.cmpb.2025.109211_b10","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.cell.2018.03.034","article-title":"Machine learning identifies stemness features associated with oncogenic dedifferentiation","volume":"173","author":"Malta","year":"2018","journal-title":"Cell"},{"key":"10.1016\/j.cmpb.2025.109211_b11","doi-asserted-by":"crossref","DOI":"10.3389\/fgene.2021.666561","article-title":"Integrative analysis of gene expression through one-class logistic regression machine learning identifies stemness features in multiple myeloma","author":"Ban","year":"2021","journal-title":"Front. Genet."},{"key":"10.1016\/j.cmpb.2025.109211_b12","article-title":"Identification and validation of a novel cuproptosis-related gene signature in multiple myeloma","volume":"11","author":"Zhang","year":"2023","journal-title":"Front. Cell Dev. Biology"},{"key":"10.1016\/j.cmpb.2025.109211_b13","article-title":"Characterization of stem cell landscape and assessing the stemness degree to aid clinical therapeutics in hematologic malignancies","volume":"14","author":"Feng","year":"2024","journal-title":"Sci. Rep."},{"issue":"5","key":"10.1016\/j.cmpb.2025.109211_b14","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1093\/jnci\/djz159","article-title":"Identification and characterization of tumor-initiating cells in multiple myeloma","volume":"112","author":"Gao","year":"2020","journal-title":"J. Natl. Cancer Inst."},{"issue":"10","key":"10.1016\/j.cmpb.2025.109211_b15","doi-asserted-by":"crossref","first-page":"2913","DOI":"10.3390\/jcm11102913","article-title":"CD24 is a prognostic marker for multiple myeloma progression and survival","volume":"11","author":"Gross Even-Zohar","year":"2022","journal-title":"J. Clin. Med."},{"key":"10.1016\/j.cmpb.2025.109211_b16","doi-asserted-by":"crossref","first-page":"1636","DOI":"10.1038\/sj.bjc.6605668","article-title":"Molecular characterisation of side population cells with cancer stem cell-like characteristics in small-cell lung cancer","volume":"102","author":"Salcido","year":"2010","journal-title":"Br. J. Cancer"},{"key":"10.1016\/j.cmpb.2025.109211_b17","series-title":"Gene Expression Profiles of Multiple Myeloma from the sorted SP\/LC and CD138+ cells (GEO: GSE109651)","author":"Zhan","year":"2019"},{"key":"10.1016\/j.cmpb.2025.109211_b18","series-title":"KEGG: Kyoto encyclopedia of genes and genomes","year":"2024"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b19","doi-asserted-by":"crossref","first-page":"10258","DOI":"10.1038\/s41598-020-66986-8","article-title":"ssGSEA score-based Ras dependency indexes derived from gene expression data reveal potential Ras addiction mechanisms with possible clinical implications","volume":"10","author":"Yi","year":"2020","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cmpb.2025.109211_b20","series-title":"The cancer genome atlas (TCGA) program data","author":"The Cancer Genome Atlas (TCGA) Research Network","year":"2025"},{"key":"10.1016\/j.cmpb.2025.109211_b21","series-title":"MMRF CoMMpass study (IA18 release)","author":"Multiple Myeloma Research Foundation (MMRF)","year":"2025"},{"key":"10.1016\/j.cmpb.2025.109211_b22","series-title":"NCBI GEO: archive for functional genomics data sets\u2013update","author":"Barrett","year":"2013"},{"key":"10.1016\/j.cmpb.2025.109211_b23","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1186\/1471-2105-9-559","article-title":"WGCNA: an R package for weighted correlation network analysis","volume":"9","author":"Langfelder","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.cmpb.2025.109211_b24","series-title":"Survival: A package for survival analysis in R","author":"Therneau","year":"2024"},{"key":"10.1016\/j.cmpb.2025.109211_b25","series-title":"Survminer: Drawing survival curves using \u2019ggplot2\u2019 (R package)","author":"Kassambara","year":"2025"},{"key":"10.1016\/j.cmpb.2025.109211_b26","series-title":"timeROC: Time-dependent receiver operating characteristic and AUC for censored survival data","author":"Blanche","year":"2013"},{"key":"10.1016\/j.cmpb.2025.109211_b27","series-title":"Boot: Bootstrap functions (R package)","author":"Canty","year":"2025"},{"key":"10.1016\/j.cmpb.2025.109211_b28","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/1471-2105-14-7","article-title":"GSVA: Gene set variation analysis for microarray and RNA-Seq data","volume":"14","author":"H\u00e4nzelmann","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.cmpb.2025.109211_b29","series-title":"GSVA: Gene set variation analysis R package (software manual \/ package)","author":"H\u00e4nzelmann","year":"2013"},{"key":"10.1016\/j.cmpb.2025.109211_b30","series-title":"GSEABase: Gene set enrichment data structures and methods (Bioconductor package)","author":"Morgan","year":"2024"},{"key":"10.1016\/j.cmpb.2025.109211_b31","first-page":"3046","article-title":"OncoPredict: an R package for predicting in vitro and in vivo drug response from transcriptomic data","volume":"37","author":"Maeser","year":"2021","journal-title":"Bioinformatics"},{"key":"10.1016\/j.cmpb.2025.109211_b32","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkv007","article-title":"Limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.cmpb.2025.109211_b33","series-title":"GEO and TCGA data integration platform","author":"Platform","year":"2024"},{"key":"10.1016\/j.cmpb.2025.109211_b34","series-title":"Ggpubr: \u2019ggplot2\u2019 based publication ready plots","author":"Kassambara","year":"2025"},{"key":"10.1016\/j.cmpb.2025.109211_b35","series-title":"Modern Applied Statistics with S","author":"Venables","year":"2002"},{"key":"10.1016\/j.cmpb.2025.109211_b36","series-title":"Muhaz: Hazard function estimation in survival analysis (R package)","author":"Winsemius","year":"2021"},{"key":"10.1016\/j.cmpb.2025.109211_b37","series-title":"Pheatmap: Pretty heatmaps (R package)","author":"Kolde","year":"2023"},{"key":"10.1016\/j.cmpb.2025.109211_b38","series-title":"reshape2: Flexibly reshape data (R package)","author":"Wickham","year":"2020"},{"key":"10.1016\/j.cmpb.2025.109211_b39","series-title":"Sva: Surrogate variable analysis","author":"Leek","year":"2025"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b40","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1093\/biostatistics\/kxj037","article-title":"Adjusting batch effects in microarray expression data using empirical Bayes methods","volume":"8","author":"Johnson","year":"2007","journal-title":"Biostatistics"},{"issue":"6","key":"10.1016\/j.cmpb.2025.109211_b41","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1093\/bioinformatics\/bts034","article-title":"The sva package for removing batch effects and other unwanted variation in high-throughput experiments","volume":"28","author":"Leek","year":"2012","journal-title":"Bioinformatics"},{"key":"10.1016\/j.cmpb.2025.109211_b42","doi-asserted-by":"crossref","first-page":"D991","DOI":"10.1093\/nar\/gks1193","article-title":"NCBI GEO: archive for functional genomics data sets\u2014update (including GEO2R tool)","volume":"41","author":"Barrett","year":"2013","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.cmpb.2025.109211_b43","series-title":"GEO2R: Interactive analysis of GEO data sets","year":"2024"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b44","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1093\/nar\/28.1.27","article-title":"KEGG: Kyoto encyclopedia of genes and genomes","volume":"28","author":"Kanehisa","year":"2000","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.cmpb.2025.109211_b45","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1038\/s41467-019-09234-6","article-title":"Metascape provides a biologist-oriented resource for the analysis of systems-level datasets","volume":"10","author":"Zhou","year":"2019","journal-title":"Nat. Commun."},{"key":"10.1016\/j.cmpb.2025.109211_b46","series-title":"A gene annotation and analysis resource","author":"Metascape","year":"2024"},{"issue":"10","key":"10.1016\/j.cmpb.2025.109211_b47","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1038\/s41591-018-0136-1","article-title":"Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response","volume":"24","author":"Jiang","year":"2018","journal-title":"Nature Med."},{"key":"10.1016\/j.cmpb.2025.109211_b48","series-title":"TIDE: Tumor immune dysfunction and exclusion analysis","year":"2024"},{"key":"10.1016\/j.cmpb.2025.109211_b49","series-title":"fmincon: Find minimum of constrained nonlinear multivariable function","author":"The MathWorks, Inc.","year":"2024"},{"key":"10.1016\/j.cmpb.2025.109211_b50","series-title":"Gene expression profiling of multiple myeloma patients included in the HOVON65\/GMMG-HD4 trial (GEO: GSE19784)","author":"Broyl","year":"2010"},{"key":"10.1016\/j.cmpb.2025.109211_b51","series-title":"MAQC-II Project: Multiple myeloma (MM) data set (GEO: GSE24080)","author":"Shi","year":"2010"},{"key":"10.1016\/j.cmpb.2025.109211_b52","series-title":"Gene expression profiles of patients with multiple myeloma who have been treated previously (GEO: GSE57317)","author":"Heuck","year":"2015"},{"issue":"6509","key":"10.1016\/j.cmpb.2025.109211_b53","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1126\/science.aaz1776","article-title":"The GTEx consortium atlas of genetic regulatory effects across human tissues","volume":"369","author":"Consortium","year":"2020","journal-title":"Science"},{"key":"10.1016\/j.cmpb.2025.109211_b54","doi-asserted-by":"crossref","first-page":"2612","DOI":"10.1038\/ncomms3612","article-title":"Inferring tumour purity and stromal and immune cell admixture using gene expression data","volume":"4","author":"Yoshihara","year":"2013","journal-title":"Nat. Commun."},{"issue":"18","key":"10.1016\/j.cmpb.2025.109211_b55","article-title":"A protocol for weighted gene co-expression network analysis with module preservation and functional enrichment analysis for tumor and normal transcriptomic data","volume":"15","author":"Nguyen","year":"2025","journal-title":"Bio Protoc"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b56","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1001057","article-title":"Is my network module preserved and reproducible?","volume":"7","author":"Langfelder","year":"2011","journal-title":"PLoS Comput. Biol."},{"issue":"11","key":"10.1016\/j.cmpb.2025.109211_b57","article-title":"A data-driven framework for simulating RNA-seq datasets with realistic variability","volume":"16","author":"Gerard","year":"2020","journal-title":"PLoS Comput. Biol."},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b58","first-page":"385","article-title":"SPsimSeq: semi-parametric simulation of bulk and single-cell RNA-seq data","volume":"21","author":"Assefa","year":"2020","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.cmpb.2025.109211_b59","series-title":"Bootstrap Methods and Their Application","author":"Davison","year":"1997"},{"issue":"1","key":"10.1016\/j.cmpb.2025.109211_b60","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":"2","key":"10.1016\/j.cmpb.2025.109211_b61","doi-asserted-by":"crossref","first-page":"R29","DOI":"10.1186\/gb-2014-15-2-r29","article-title":"Voom: Precision weights unlock linear model analysis tools for RNA-seq read counts","volume":"15","author":"Law","year":"2014","journal-title":"Genome Biology"},{"issue":"7","key":"10.1016\/j.cmpb.2025.109211_b62","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkv007","article-title":"Limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.cmpb.2025.109211_b63","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1158\/1535-7163.MCT-11-1040","article-title":"DNA damage repair pathways in cancer stem cells","volume":"11","author":"Maugeri-Sacca","year":"2012","journal-title":"Mol. Cancer Ther."},{"key":"10.1016\/j.cmpb.2025.109211_b64","doi-asserted-by":"crossref","first-page":"5589","DOI":"10.1158\/0008-5472.CAN-21-1606","article-title":"Epigenetic alterations and mechanisms that drive resistance to targeted cancer therapies","volume":"81","author":"Wajapeyee","year":"2021","journal-title":"Cancer Res."},{"key":"10.1016\/j.cmpb.2025.109211_b65","doi-asserted-by":"crossref","first-page":"9245","DOI":"10.1158\/0008-5472.CAN-09-2802","article-title":"Cancer stem cells and aneuploid populations within developing tumors are the major determinants of tumor dormancy","volume":"69","author":"Kusumbe","year":"2009","journal-title":"Cancer Res."},{"key":"10.1016\/j.cmpb.2025.109211_b66","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1007\/s12015-020-09995-4","article-title":"Emerging importance of survivin in stem cells and cancer: the development of new cancer therapeutics","volume":"16","author":"Warrier","year":"2020","journal-title":"Stem Cell Rev. Rep."},{"key":"10.1016\/j.cmpb.2025.109211_b67","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1002\/path.5222","article-title":"Autophagy, cancer stem cells and drug resistance","volume":"247","author":"Smith","year":"2019","journal-title":"J. Pathol."},{"key":"10.1016\/j.cmpb.2025.109211_b68","doi-asserted-by":"crossref","first-page":"e875","DOI":"10.1038\/cddis.2013.407","article-title":"Acquisition of epithelial\u2013mesenchymal transition and cancer stem cell phenotypes is associated with activation of the PI3K\/Akt\/mTOR pathway in prostate cancer radioresistance","volume":"4","author":"Chang","year":"2013","journal-title":"Cell Death Dis."},{"key":"10.1016\/j.cmpb.2025.109211_b69","article-title":"PI3K\/Akt\/mTOR signaling pathway in cancer stem cells","volume":"237","author":"Ebrahimi","year":"2022","journal-title":"Pathol.-Res. Pr."},{"key":"10.1016\/j.cmpb.2025.109211_b70","doi-asserted-by":"crossref","DOI":"10.2147\/OTT.S249895","article-title":"A 5-gene stemness score for rapid determination of risk in multiple myeloma","author":"Bai","year":"2020","journal-title":"OncoTargets Ther."},{"key":"10.1016\/j.cmpb.2025.109211_b71","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2022.918778","article-title":"ALDH1A1 in cancers: bidirectional function, drug resistance, and regulatory mechanism","volume":"12","author":"Yue","year":"2022","journal-title":"Front. Oncol."},{"issue":"2","key":"10.1016\/j.cmpb.2025.109211_b72","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1038\/labinvest.2009.127","article-title":"ALDH1A1 is a marker for malignant prostate stem cells and predictor of prostate cancer patients\u2019 outcome","volume":"90","author":"Li","year":"2010","journal-title":"Lab. Invest."}],"container-title":["Computer Methods and Programs in Biomedicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260725006261?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0169260725006261?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T08:37:37Z","timestamp":1781771857000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0169260725006261"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":72,"alternative-id":["S0169260725006261"],"URL":"https:\/\/doi.org\/10.1016\/j.cmpb.2025.109211","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.175037115.51802300\/v1","asserted-by":"object"}]},"ISSN":["0169-2607"],"issn-type":[{"value":"0169-2607","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Machine learning-assisted prognosis of multiple myeloma side population cells via SRGs and OCLR stemness index","name":"articletitle","label":"Article Title"},{"value":"Computer Methods and Programs in Biomedicine","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cmpb.2025.109211","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"109211"}}