{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T07:45:55Z","timestamp":1726127155273},"reference-count":102,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2018,7,1]],"date-time":"2018-07-01T00:00:00Z","timestamp":1530403200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Biomedical Informatics"],"published-print":{"date-parts":[[2018,7]]},"DOI":"10.1016\/j.jbi.2018.06.001","type":"journal-article","created":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T17:00:23Z","timestamp":1527872423000},"page":"87-96","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":104,"special_numbering":"C","title":["Patient similarity for precision medicine: A systematic review"],"prefix":"10.1016","volume":"83","author":[{"given":"E.","family":"Parimbelli","sequence":"first","affiliation":[]},{"given":"S.","family":"Marini","sequence":"additional","affiliation":[]},{"given":"L.","family":"Sacchi","sequence":"additional","affiliation":[]},{"given":"R.","family":"Bellazzi","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.jbi.2018.06.001_b0005","series-title":"Clinical Practice Guidelines We Can Trust","author":"Steinberg","year":"2011"},{"key":"10.1016\/j.jbi.2018.06.001_b0010","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1056\/NEJMp1500523","article-title":"A new initiative on precision medicine","volume":"372","author":"Collins","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0015","doi-asserted-by":"crossref","first-page":"2229","DOI":"10.1056\/NEJMsb1503104","article-title":"Precision medicine\u2013personalized, problematic, and promising","volume":"372","author":"Jameson","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0020","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1186\/s12859-015-0680-3","article-title":"MVDA: a multi-view genomic data integration methodology","volume":"16","author":"Serra","year":"2015","journal-title":"BMC Bioinf."},{"key":"10.1016\/j.jbi.2018.06.001_b0025","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.1016\/j.ebiom.2015.07.017","article-title":"Integration of copy number and transcriptomics provides risk stratification in prostate cancer: a discovery and validation cohort study","volume":"2","author":"Ross-Adams","year":"2015","journal-title":"EBioMedicine"},{"key":"10.1016\/j.jbi.2018.06.001_b0030","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1186\/s12864-015-2170-4","article-title":"Integrative phenotyping framework (iPF): integrative clustering of multiple omics data identifies novel lung disease subphenotypes","volume":"16","author":"Kim","year":"2015","journal-title":"BMC Genomics"},{"key":"10.1016\/j.jbi.2018.06.001_b0035","doi-asserted-by":"crossref","DOI":"10.1053\/j.gastro.2011.12.005","article-title":"Genomic and genetic characterization of cholangiocarcinoma identifies therapeutic targets for tyrosine kinase inhibitors","volume":"142","author":"Andersen","year":"2012","journal-title":"Gastroenterology"},{"key":"10.1016\/j.jbi.2018.06.001_b0040","doi-asserted-by":"crossref","first-page":"4174","DOI":"10.1158\/1078-0432.CCR-12-3690","article-title":"A poor prognosis subtype of HNSCC is consistently observed across methylome, transcriptome, and miRNome analysis","volume":"19","author":"Jung","year":"2013","journal-title":"Clin. Cancer Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0045","doi-asserted-by":"crossref","first-page":"69","DOI":"10.2174\/1567205012666141218123829","article-title":"Predicting progression from cognitive impairment to Alzheimer\u2019s disease with the disease state index","volume":"12","author":"Hall","year":"2015","journal-title":"Curr. Alzheimer Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0050","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1038\/nm.3175","article-title":"A colorectal cancer classification system that associates cellular phenotype and responses to therapy","volume":"19","author":"Sadanandam","year":"2013","journal-title":"Nat. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0055","doi-asserted-by":"crossref","first-page":"40200","DOI":"10.18632\/oncotarget.9571","article-title":"Big data and computational biology strategy for personalized prognosis","volume":"7","author":"Ow","year":"2016","journal-title":"Oncotarget"},{"key":"10.1016\/j.jbi.2018.06.001_b0060","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1038\/nrc.2016.56","article-title":"Biomarker development in the precision medicine era: lung cancer as a case study","volume":"16","author":"Vargas","year":"2016","journal-title":"Nat. Rev. Cancer"},{"key":"10.1016\/j.jbi.2018.06.001_b0065","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1007\/s10926-012-9370-4","article-title":"Distressed, immobilized, or lacking employer support? A sub-classification of acute work-related low back pain","volume":"22","author":"Reme","year":"2012","journal-title":"J. Occup. Rehabil."},{"key":"10.1016\/j.jbi.2018.06.001_b0070","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1097\/AJP.0000000000000080","article-title":"Low back pain patient subgroups in primary care: pain characteristics, psychosocial determinants, and health care utilization","volume":"30","author":"Hirsch","year":"2014","journal-title":"Clin. J. Pain"},{"key":"10.1016\/j.jbi.2018.06.001_b0075","doi-asserted-by":"crossref","first-page":"255","DOI":"10.4310\/SII.2016.v9.n3.a1","article-title":"Stratified psychiatry via convexity-based clustering with applications towards moderator analysis","volume":"9","author":"Tarpey","year":"2016","journal-title":"Stat. Interf."},{"key":"10.1016\/j.jbi.2018.06.001_b0080","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.nicl.2013.11.002","article-title":"Dissecting psychiatric spectrum disorders by generative embedding","volume":"4","author":"Brodersen","year":"2014","journal-title":"Neuroimage Clin."},{"key":"10.1016\/j.jbi.2018.06.001_b0085","article-title":"Magnetic resonance perfusion image features uncover an angiogenic subgroup of glioblastoma patients with poor survival and better response to antiangiogenic treatment","author":"Liu","year":"2016","journal-title":"Neuro-Oncology"},{"key":"10.1016\/j.jbi.2018.06.001_b0090","doi-asserted-by":"crossref","first-page":"1648","DOI":"10.1038\/s41598-017-01931-w","article-title":"Precision radiology: predicting longevity using feature engineering and deep learning methods in a radiomics framework","volume":"7","author":"Oakden-Rayner","year":"2017","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jbi.2018.06.001_b0095","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1109\/TMI.2014.2365436","article-title":"Analysis of structural similarity in mammograms for detection of bilateral asymmetry","volume":"34","author":"Casti","year":"2015","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.jbi.2018.06.001_b0100","doi-asserted-by":"crossref","first-page":"e51871","DOI":"10.1371\/journal.pone.0051871","article-title":"Mismatch negativity\/P3a complex in young people with psychiatric disorders: a cluster analysis","volume":"7","author":"Kaur","year":"2012","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0105","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1049\/iet-syb.2015.0011","article-title":"HeartSearcher: finds patients with similar arrhythmias based on heartbeat classification","volume":"9","author":"Park","year":"2015","journal-title":"IET Syst. Biol."},{"key":"10.1016\/j.jbi.2018.06.001_b0110","doi-asserted-by":"crossref","first-page":"e1001453","DOI":"10.1371\/journal.pmed.1001453","article-title":"Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value","volume":"10","author":"Marisa","year":"2013","journal-title":"PLoS Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0115","doi-asserted-by":"crossref","first-page":"5533","DOI":"10.1158\/1078-0432.CCR-13-0799","article-title":"Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes","volume":"19","author":"Masuda","year":"2013","journal-title":"Clin. Cancer Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0120","doi-asserted-by":"crossref","first-page":"1393","DOI":"10.1016\/j.molonc.2014.05.010","article-title":"Long noncoding RNA profiles identify five distinct molecular subtypes of colorectal cancer with clinical relevance","volume":"8","author":"Chen","year":"2014","journal-title":"Mol. Oncol."},{"key":"10.1016\/j.jbi.2018.06.001_b0125","doi-asserted-by":"crossref","first-page":"5116","DOI":"10.1158\/1078-0432.CCR-13-0928","article-title":"Identification of transcriptional subgroups in EGFR-mutated and EGFR\/KRAS wild-type lung adenocarcinoma reveals Gene signatures associated with patient outcome","volume":"19","author":"Planck","year":"2013","journal-title":"Clin. Cancer Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0130","doi-asserted-by":"crossref","DOI":"10.1186\/s13058-017-0812-y","article-title":"OSBREAC, Integrative clustering reveals a novel split in the luminal A subtype of breast cancer with impact on outcome","volume":"19","author":"Aure","year":"2017","journal-title":"Breast Cancer Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0135","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1016\/S2213-2600(17)30294-1","article-title":"Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study","volume":"5","author":"Scicluna","year":"2017","journal-title":"Lancet Respir. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0140","doi-asserted-by":"crossref","first-page":"1607","DOI":"10.1097\/CCM.0000000000002548","article-title":"Identifying distinct subgroups of ICU patients: a machine learning approach","volume":"45","author":"Vranas","year":"2017","journal-title":"Crit. Care Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0145","doi-asserted-by":"crossref","first-page":"803","DOI":"10.2307\/2532201","article-title":"Model-based Gaussian and non-Gaussian clustering","volume":"49","author":"Banfield","year":"1993","journal-title":"Biometrics"},{"key":"10.1016\/j.jbi.2018.06.001_b0150","doi-asserted-by":"crossref","DOI":"10.1109\/JBHI.2016.2514264","article-title":"Patient stratification using electronic health records from a chronic disease management program","author":"Chen","year":"2016","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0155","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.eurpsy.2014.10.005","article-title":"Influence of birth cohort on age of onset cluster analysis in bipolar I disorder","volume":"30","author":"Bauer","year":"2015","journal-title":"Eur. Psychiatry"},{"key":"10.1016\/j.jbi.2018.06.001_b0160","doi-asserted-by":"crossref","first-page":"2651","DOI":"10.1093\/bioinformatics\/btx303","article-title":"Accounting for tumor purity improves cancer subtype classification from DNA methylation data","volume":"33","author":"Zhang","year":"2017","journal-title":"Bioinformatics"},{"key":"10.1016\/j.jbi.2018.06.001_b0165","first-page":"401","article-title":"Phenotyping hypotensive patients in critical care using hospital discharge summaries","volume":"2017","author":"Dai","year":"2017","journal-title":"IEEE EMBS Int. Conf. Biomed. Health Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0170","doi-asserted-by":"crossref","first-page":"e0141171","DOI":"10.1371\/journal.pone.0141171","article-title":"T cell transcriptomes describe patient subtypes in systemic lupus erythematosus","volume":"10","author":"Bradley","year":"2015","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0175","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1093\/bioinformatics\/btv692","article-title":"An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types","volume":"32","author":"Park","year":"2016","journal-title":"Bioinformatics"},{"key":"10.1016\/j.jbi.2018.06.001_b0180","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0137132","article-title":"Clustering of expression data in chronic lymphocytic leukemia reveals new molecular subdivisions","volume":"10","author":"Yepes","year":"2015","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0185","first-page":"127","article-title":"Prechemotherapy touch sensation deficits predict oxaliplatin-induced neuropathy in patients with colorectal cancer","volume":"90","author":"Wang","year":"2016","journal-title":"Oncology (Switzerland)."},{"issue":"Suppl. 1","key":"10.1016\/j.jbi.2018.06.001_b0190","doi-asserted-by":"crossref","first-page":"S1","DOI":"10.1186\/1755-8794-7-S1-S1","article-title":"Concordance of deregulated mechanisms unveiled in underpowered experiments: PTBP1 knockdown case study","volume":"7","author":"Gardeux","year":"2014","journal-title":"BMC Med. Genomics"},{"key":"10.1016\/j.jbi.2018.06.001_b0195","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/j.ymeth.2014.03.005","article-title":"Breast cancer patient stratification using a molecular regularized consensus clustering method","volume":"67","author":"Wang","year":"2014","journal-title":"Methods"},{"key":"10.1016\/j.jbi.2018.06.001_b0200","first-page":"345","article-title":"Bayesian biclustering for patient stratification","volume":"21","author":"Khakabimamaghani","year":"2016","journal-title":"Pac. Symp. Biocomput."},{"key":"10.1016\/j.jbi.2018.06.001_b0205","doi-asserted-by":"crossref","first-page":"e84955","DOI":"10.1371\/journal.pone.0084955","article-title":"Clustering gene expression regulators: new approach to disease subtyping","volume":"9","author":"Pyatnitskiy","year":"2014","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0210","doi-asserted-by":"crossref","first-page":"311ra174","DOI":"10.1126\/scitranslmed.aaa9364","article-title":"Identification of type 2 diabetes subgroups through topological analysis of patient similarity","volume":"7","author":"Li","year":"2015","journal-title":"Sci. Transl. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0215","article-title":"Identifying cancer subtypes from miRNA-TFmRNA regulatory networks and expression data","volume":"11","author":"Xu","year":"2016","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0220","article-title":"Clustering of longitudinal data by using an extended baseline: a new method for treatment efficacy clustering in longitudinal data","author":"Schramm","year":"2015","journal-title":"Stat. Methods Med. Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0225","doi-asserted-by":"crossref","DOI":"10.1118\/1.4764900","article-title":"Voxel clustering for quantifying PET-based treatment response assessment","volume":"40","author":"Schreibmann","year":"2013","journal-title":"Med. Phys."},{"key":"10.1016\/j.jbi.2018.06.001_b0230","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1038\/nature11412","article-title":"Comprehensive molecular portraits of human breast tumours","volume":"490","author":"Cancer Genome Atlas Network","year":"2012","journal-title":"Nature"},{"key":"10.1016\/j.jbi.2018.06.001_b0235","first-page":"132","article-title":"Towards personalized medicine: leveraging patient similarity and drug similarity analytics","volume":"2014","author":"Zhang","year":"2014","journal-title":"AMIA Jt. Summits Transl. Sci. Proc."},{"key":"10.1016\/j.jbi.2018.06.001_b0240","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.jbi.2015.01.009","article-title":"Adaptive semi-supervised recursive tree partitioning: the ART towards large scale patient indexing in personalized healthcare","volume":"55","author":"Wang","year":"2015","journal-title":"J. Biomed. Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0245","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1109\/JBHI.2015.2425365","article-title":"PSF: a unified patient similarity evaluation framework through metric learning with weak supervision","volume":"19","author":"Wang","year":"2015","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0250","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/JBHI.2013.2274281","article-title":"Similarity measure between patient traces for clinical pathway analysis: problem method, and applications","volume":"18","author":"Huang","year":"2014","journal-title":"IEEE J. Biomed. Health Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0255","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.jbi.2015.03.003","article-title":"towards a PBMC \u201cvirogram assay\u201d for precision medicine: concordance between ex vivo and in vivo viral infection transcriptomes","volume":"55","author":"Gardeux","year":"2015","journal-title":"J. Biomed. Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0260","doi-asserted-by":"crossref","first-page":"i293","DOI":"10.1093\/bioinformatics\/btv253","article-title":"Dynamic changes of RNA-sequencing expression for precision medicine: N-of-1-pathways Mahalanobis distance within pathways of single subjects predicts breast cancer survival","volume":"31","author":"Schissler","year":"2015","journal-title":"Bioinformatics"},{"key":"10.1016\/j.jbi.2018.06.001_b0265","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.jbi.2016.12.009","article-title":"kMEn: analyzing noisy and bidirectional transcriptional pathway responses in single subjects","volume":"66","author":"Li","year":"2017","journal-title":"J. Biomed. Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0270","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/TSIPN.2015.2429471","article-title":"Diffusion and superposition distances for signals supported on networks","volume":"1","author":"Segarra","year":"2015","journal-title":"IEEE Trans. Signal Inf. Process. Networks"},{"key":"10.1016\/j.jbi.2018.06.001_b0275","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1109\/TNSRE.2014.2362862","article-title":"Clinical gait analysis: comparing explicit state duration HMMs using a reference-based index","volume":"23","author":"Karg","year":"2015","journal-title":"IEEE Trans. Neural Syst. Rehabilitation Eng."},{"key":"10.1016\/j.jbi.2018.06.001_b0280","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1162\/NECO_a_00235","article-title":"Quantifying statistical interdependence, Part III: N gt; 2 point processes","volume":"24","author":"Dauwels","year":"2012","journal-title":"Neural Comput."},{"key":"10.1016\/j.jbi.2018.06.001_b0285","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/JBHI.2014.2375491","article-title":"Content-based image retrieval by metric learning from radiology reports: application to interstitial lung diseases","volume":"20","author":"Ramos","year":"2016","journal-title":"IEEE J. Biomed. Health. Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0290","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.artmed.2013.04.008","article-title":"Subpopulation-specific confidence designation for more informative biomedical classification","volume":"58","author":"Zhang","year":"2013","journal-title":"Artif. Intell. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0295","doi-asserted-by":"crossref","first-page":"W154","DOI":"10.1093\/nar\/gkw378","article-title":"ICM: a web server for integrated clustering of multi-dimensional biomedical data","volume":"44","author":"He","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0300","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1038\/nmeth.2810","article-title":"Similarity network fusion for aggregating data types on a genomic scale","volume":"11","author":"Wang","year":"2014","journal-title":"Nat. Methods"},{"key":"10.1016\/j.jbi.2018.06.001_b0305","doi-asserted-by":"crossref","first-page":"2906","DOI":"10.1093\/bioinformatics\/btp543","article-title":"Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis","volume":"25","author":"Shen","year":"2009","journal-title":"Bioinformatics"},{"key":"10.1016\/j.jbi.2018.06.001_b0310","first-page":"321","article-title":"Patient-specific data fusion for cancer stratification and personalised treatment","volume":"21","author":"Gligorijevi\u0107","year":"2016","journal-title":"Pac. Symp. Biocomput."},{"key":"10.1016\/j.jbi.2018.06.001_b0315","doi-asserted-by":"crossref","first-page":"24949","DOI":"10.1038\/srep24949","article-title":"Pan-cancer subtyping in a 2D-map shows substructures that are driven by specific combinations of molecular characteristics","volume":"6","author":"Taskesen","year":"2016","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jbi.2018.06.001_b0320","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s13073-016-0281-4","article-title":"CoINcIDE: a framework for discovery of patient subtypes across multiple datasets","volume":"8","author":"Planey","year":"2016","journal-title":"Genome Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0325","doi-asserted-by":"crossref","first-page":"e0162407","DOI":"10.1371\/journal.pone.0162407","article-title":"A network-based data integration approach to support drug repurposing and multi-target therapies in triple negative breast cancer","volume":"11","author":"Vitali","year":"2016","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0330","doi-asserted-by":"crossref","first-page":"e0164940","DOI":"10.1371\/journal.pone.0164940","article-title":"A data fusion approach to enhance association study in epilepsy","volume":"11","author":"Marini","year":"2016","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0335","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1109\/TCBB.2016.2621769","article-title":"Cancer subtype discovery based on integrative model of multigenomic data","volume":"14","author":"Ge","year":"2017","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"key":"10.1016\/j.jbi.2018.06.001_b0340","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/btx464","article-title":"Towards clinically more relevant dissection of patient heterogeneity via survival based bayesian clustering","author":"Ahmad","year":"2017","journal-title":"Bioinformatics"},{"key":"10.1016\/j.jbi.2018.06.001_b0345","first-page":"532","article-title":"Algorithmic summaries of perioperative blood pressure fluctuations","volume":"228","author":"Toddenroth","year":"2016","journal-title":"Stud. Health Technol. Inf."},{"key":"10.1016\/j.jbi.2018.06.001_b0350","doi-asserted-by":"crossref","first-page":"2750","DOI":"10.1172\/JCI45014","article-title":"Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies","volume":"121","author":"Lehmann","year":"2011","journal-title":"J. Clin. Invest."},{"key":"10.1016\/j.jbi.2018.06.001_b0355","doi-asserted-by":"crossref","first-page":"5806","DOI":"10.1158\/1078-0432.CCR-12-0857","article-title":"Profiles of genomic instability in high-grade serous ovarian cancer predict treatment outcome","volume":"18","author":"Wang","year":"2012","journal-title":"Clin. Cancer Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0360","doi-asserted-by":"crossref","first-page":"e64260","DOI":"10.1371\/journal.pone.0064260","article-title":"Actionable gene expression-based patient stratification for molecular targeted therapy in hepatocellular carcinoma","volume":"8","author":"Kwon","year":"2013","journal-title":"PLoS One"},{"key":"10.1016\/j.jbi.2018.06.001_b0365","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1039\/C5IB00071H","article-title":"MicroC(3): an ex vivo microfluidic cis-coculture assay to test chemosensitivity and resistance of patient multiple myeloma cells","volume":"7","author":"Pak","year":"2015","journal-title":"Integr. Biol. (Camb.)"},{"key":"10.1016\/j.jbi.2018.06.001_b0370","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1002\/mpr.1390","article-title":"Local control for identifying subgroups of interest in observational research: persistence of treatment for major depressive disorder","volume":"22","author":"Faries","year":"2013","journal-title":"Int. J. Methods Psychiatr. Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0375","doi-asserted-by":"crossref","first-page":"1340","DOI":"10.1038\/npp.2013.301","article-title":"Influence of RGS2 on sertraline treatment for social anxiety disorder","volume":"39","author":"Stein","year":"2014","journal-title":"Neuropsychopharmacology."},{"key":"10.1016\/j.jbi.2018.06.001_b0380","doi-asserted-by":"crossref","first-page":"5740","DOI":"10.1118\/1.4742848","article-title":"A novel conformity index for intensity modulated radiation therapy plan evaluation","volume":"39","author":"Cheung","year":"2012","journal-title":"Med. Phys."},{"key":"10.1016\/j.jbi.2018.06.001_b0385","doi-asserted-by":"crossref","first-page":"3945","DOI":"10.1088\/0031-9155\/57\/12\/3945","article-title":"Automatic bladder segmentation on CBCT for multiple plan ART of bladder cancer using a patient-specific bladder model","volume":"57","author":"Chai","year":"2012","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.jbi.2018.06.001_b0390","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1002\/jso.23525","article-title":"The clinical implications of integrating additional prognostic factors into the TNM","volume":"109","author":"Henson","year":"2014","journal-title":"J. Surg. Oncol."},{"key":"10.1016\/j.jbi.2018.06.001_b0395","doi-asserted-by":"crossref","first-page":"1572","DOI":"10.1016\/j.jpsychires.2013.07.021","article-title":"Psychiatric patient stratification using biosignatures based on cerebrospinal fluid protein expression clusters","volume":"47","author":"Maccarrone","year":"2013","journal-title":"J. Psychiatr. Res."},{"key":"10.1016\/j.jbi.2018.06.001_b0400","first-page":"1","article-title":"Asthma phenotypes in childhood","author":"Deliu","year":"2016","journal-title":"Expert Rev. Clin. Immunol."},{"key":"10.1016\/j.jbi.2018.06.001_b0405","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1513\/AnnalsATS.201403-125OC","article-title":"Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints, identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis","volume":"12","author":"Rennard","year":"2015","journal-title":"Ann. Am. Thorac. Soc."},{"key":"10.1016\/j.jbi.2018.06.001_b0410","article-title":"Phenotypes in obstructive sleep apnea: a definition, examples and evolution of approaches","author":"Zinchuk","year":"2016","journal-title":"Sleep Med. Rev."},{"key":"10.1016\/j.jbi.2018.06.001_b0415","doi-asserted-by":"crossref","first-page":"5394","DOI":"10.1073\/pnas.1601591113","article-title":"Big data visualization identifies the multidimensional molecular landscape of human gliomas","volume":"113","author":"Bolouri","year":"2016","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"10.1016\/j.jbi.2018.06.001_b0420","doi-asserted-by":"crossref","DOI":"10.3389\/fphys.2016.00561","article-title":"Patient similarity: emerging concepts in systems and precision medicine","volume":"7","author":"Brown","year":"2016","journal-title":"Front. Physiol."},{"key":"10.1016\/j.jbi.2018.06.001_b0425","series-title":"Clinical Decision Support: the Road to a Broad Adoption","year":"2014"},{"key":"10.1016\/j.jbi.2018.06.001_b0430","unstructured":"WHO, Disease burden - Estimates for 2000\u20132015, n.d. (accessed January 31, 2018)."},{"issue":"2017","key":"10.1016\/j.jbi.2018.06.001_b0435","first-page":"524","article-title":"Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015: a systematic analysis for the global burden of disease study","volume":"3","author":"Global Burden of Disease Cancer Collaboration","year":"1990","journal-title":"JAMA Oncol."},{"key":"10.1016\/j.jbi.2018.06.001_b0440","doi-asserted-by":"crossref","first-page":"e442","DOI":"10.1371\/journal.pmed.0030442","article-title":"Projections of global mortality and burden of disease from 2002 to 2030","volume":"3","author":"Mathers","year":"2006","journal-title":"PLoS Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0445","unstructured":"UNICEF, World Health Organization, Diarrhoea: Why Children are Still Dying and What Can be Done, UNICEF, World Health Organization, New York, 2009."},{"key":"10.1016\/j.jbi.2018.06.001_b0450","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1136\/amiajnl-2012-000892","article-title":"Clinical decision support for genetically guided personalized medicine: a systematic review","volume":"20","author":"Welch","year":"2013","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.jbi.2018.06.001_b0455","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1093\/jamia\/ocv213","article-title":"An informatics research agenda to support precision medicine: seven key areas","volume":"23","author":"Tenenbaum","year":"2016","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"10.1016\/j.jbi.2018.06.001_b0460","doi-asserted-by":"crossref","first-page":"e7","DOI":"10.2196\/medinform.6730","article-title":"Patient similarity in prediction models based on health data: a scoping review","volume":"5","author":"Sharafoddini","year":"2017","journal-title":"JMIR Med Inform."},{"key":"10.1016\/j.jbi.2018.06.001_b0465","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1214\/09-STS307","article-title":"Population structure and cryptic relatedness in genetic association studies","volume":"24","author":"Astle","year":"2009","journal-title":"Stat. Sci."},{"key":"10.1016\/j.jbi.2018.06.001_b0470","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/ng1702","article-title":"A unified mixed-model method for association mapping that accounts for multiple levels of relatedness","volume":"38","author":"Yu","year":"2006","journal-title":"Nat. Genet."},{"key":"10.1016\/j.jbi.2018.06.001_b0475","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1038\/ng.546","article-title":"Mixed linear model approach adapted for genome-wide association studies","volume":"42","author":"Zhang","year":"2010","journal-title":"Nat. Genet."},{"key":"10.1016\/j.jbi.2018.06.001_b0480","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1038\/nrg2813","article-title":"New approaches to population stratification in genome-wide association studies","volume":"11","author":"Price","year":"2010","journal-title":"Nat. Rev. Genet."},{"key":"10.1016\/j.jbi.2018.06.001_b0485","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1186\/1746-4811-9-29","article-title":"The advantages and limitations of trait analysis with GWAS: a review","volume":"9","author":"Korte","year":"2013","journal-title":"Plant Methods"},{"key":"10.1016\/j.jbi.2018.06.001_b0490","doi-asserted-by":"crossref","first-page":"26094","DOI":"10.1038\/srep26094","article-title":"Deep patient: an unsupervised representation to predict the future of patients from the electronic health records","volume":"6","author":"Miotto","year":"2016","journal-title":"Sci. Rep."},{"key":"10.1016\/j.jbi.2018.06.001_b0495","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1109\/TCBB.2014.2377729","article-title":"Integrative data analysis of multi-platform cancer data with a multimodal deep learning approach","volume":"12","author":"Liang","year":"2015","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"10.1016\/j.jbi.2018.06.001_b0500","unstructured":"A.K. Goel, B. Diaz-Agudo, What\u2019s Hot in Case-Based Reasoning, AAAI, 2017, pp. 5067\u20135069. (accessed July 11, 2017)."},{"key":"10.1016\/j.jbi.2018.06.001_b0505","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.artmed.2017.02.003","article-title":"A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis","volume":"77","author":"Gu","year":"2017","journal-title":"Artif. Intell. Med."},{"key":"10.1016\/j.jbi.2018.06.001_b0510","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.compbiomed.2017.05.010","article-title":"A CBR framework with gradient boosting based feature selection for lung cancer subtype classification","volume":"86","author":"Ramos-Gonz\u00e1lez","year":"2017","journal-title":"Comput. Biol. Med."}],"container-title":["Journal of Biomedical Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1532046418301072?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1532046418301072?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,7,7]],"date-time":"2024-07-07T07:05:56Z","timestamp":1720335956000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1532046418301072"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":102,"alternative-id":["S1532046418301072"],"URL":"https:\/\/doi.org\/10.1016\/j.jbi.2018.06.001","relation":{},"ISSN":["1532-0464"],"issn-type":[{"value":"1532-0464","type":"print"}],"subject":[],"published":{"date-parts":[[2018,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Patient similarity for precision medicine: A systematic review","name":"articletitle","label":"Article Title"},{"value":"Journal of Biomedical Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jbi.2018.06.001","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2018 Elsevier Inc.","name":"copyright","label":"Copyright"}]}}