{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,6]],"date-time":"2026-11-06T22:16:15Z","timestamp":1794003375026,"version":"4.8.0"},"reference-count":84,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:00:00Z","timestamp":1705536000000},"content-version":"vor","delay-in-days":57,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Brain Foundation and the Spinnaker Health Research Foundation"},{"DOI":"10.13039\/501100019111","name":"Perron Institute for Neurological and Translational Science","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100019111","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of muscle disorders including adult and juvenile dermatomyositis, polymyositis, immune-mediated necrotising myopathy and sporadic inclusion body myositis, all of which present with variable symptoms and disease progression. The identification of effective biomarkers for IIMs has been challenging due to the heterogeneity between IIMs and within IIM subgroups, but recent advances in machine learning (ML) techniques have shown promises in identifying novel biomarkers. This paper reviews recent studies on potential biomarkers for IIM and evaluates their clinical utility. We also explore how data analytic tools and ML algorithms have been used to identify biomarkers, highlighting their potential to advance our understanding and diagnosis of IIM and improve patient outcomes. Overall, ML techniques have great potential to revolutionize biomarker discovery in IIMs and lead to more effective diagnosis and treatment.<\/jats:p>","DOI":"10.1093\/bib\/bbad514","type":"journal-article","created":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T02:05:02Z","timestamp":1705629902000},"source":"Crossref","is-referenced-by-count":21,"title":["From data to diagnosis: how machine learning is revolutionizing biomarker discovery in idiopathic inflammatory myopathies"],"prefix":"10.1093","volume":"25","author":[{"given":"Emily","family":"McLeish","sequence":"first","affiliation":[{"name":"Murdoch University , Centre for Molecular Medicine and Innovative Therapeutics, , Australia"},{"name":"Murdoch, Western Australia (WA) , Centre for Molecular Medicine and Innovative Therapeutics, , Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nataliya","family":"Slater","sequence":"additional","affiliation":[{"name":"Murdoch University , Centre for Molecular Medicine and Innovative Therapeutics, , Australia"},{"name":"Murdoch, Western Australia (WA) , Centre for Molecular Medicine and Innovative Therapeutics, , Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frank L","family":"Mastaglia","sequence":"additional","affiliation":[{"name":"Perron Institute for Neurological and Translational Science , Nedlands, WA , Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Merrilee","family":"Needham","sequence":"additional","affiliation":[{"name":"Murdoch University , Centre for Molecular Medicine and Innovative Therapeutics, , Australia"},{"name":"Murdoch, Western Australia (WA) , Centre for Molecular Medicine and Innovative Therapeutics, , Australia"},{"name":"Perron Institute for Neurological and Translational Science , Nedlands, WA , Australia"},{"name":"University of Notre Dame Australia , School of Medicine, Fremantle, WA , Australia"},{"name":"Fiona Stanley Hospital , Department of Neurology, Murdoch, WA , Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6081-8494","authenticated-orcid":false,"given":"Jerome D","family":"Coudert","sequence":"additional","affiliation":[{"name":"Murdoch University, Centre for Molecular Medicine and Innovative Therapeutics , Murdoch, Western Australia, WA, Australia"},{"name":"Perron Institute for Neurological and Translational Science , Nedlands, WA, Australia"},{"name":"University of Notre Dame Australia, School of Medicine , Fremantle, WA, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"issue":"12","key":"2024030618341166600_ref1","doi-asserted-by":"crossref","first-page":"e90","DOI":"10.1136\/annrheumdis-2017-212774","article-title":"Performance of the 2017 European league against rheumatism\/American College of Rheumatology Classification Criteria for adult and juvenile idiopathic inflammatory myopathies in clinical practice","volume":"77","author":"Ho\u010devar","year":"2018","journal-title":"Ann Rheum Dis"},{"key":"2024030618341166600_ref2","volume-title":"Best (Biomarkers, Endpoints, and Other Tools) Resource","author":"Group F-NBW","year":"2016"},{"issue":"4","key":"2024030618341166600_ref3","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1093\/jnen\/nlaa006","article-title":"Anti-Hmgcr antibody-positive myopathy shows Bcl-2-positive inflammation and lymphocytic accumulations","volume":"79","author":"Kurashige","year":"2020","journal-title":"J Neuropathol Exp Neurol"},{"key":"2024030618341166600_ref4","doi-asserted-by":"crossref","first-page":"554","DOI":"10.3389\/fneur.2019.00554","article-title":"Biomarkers in inflammatory myopathies-an expanded definition","volume":"10","author":"Benveniste","year":"2019","journal-title":"Front Neurol"},{"issue":"5","key":"2024030618341166600_ref5","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1002\/ana.20464","article-title":"Interferon-alpha\/beta-mediated innate immune mechanisms in dermatomyositis","volume":"57","author":"Greenberg","year":"2005","journal-title":"Ann Neurol"},{"issue":"6","key":"2024030618341166600_ref6","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.1093\/brain\/awy105","article-title":"Jak inhibitor improves type I interferon induced damage: proof of concept in dermatomyositis","volume":"141","author":"Ladislau","year":"2018","journal-title":"Brain"},{"issue":"5","key":"2024030618341166600_ref7","doi-asserted-by":"crossref","first-page":"858","DOI":"10.1002\/art.41602","article-title":"Study of tofacitinib in refractory dermatomyositis: an open-label pilot study of ten patients","volume":"73","author":"Paik","year":"2021","journal-title":"Arthritis Rheumatol"},{"issue":"1","key":"2024030618341166600_ref8","doi-asserted-by":"crossref","first-page":"101486","DOI":"10.1016\/j.berh.2020.101486","article-title":"Pitfalls in the diagnosis of myositis","volume":"34","author":"Chinoy","year":"2020","journal-title":"Best Pract Res Clin Rheumatol"},{"issue":"4","key":"2024030618341166600_ref9","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1002\/cpt.1796","article-title":"An introduction to machine learning","volume":"107","author":"Badillo","year":"2020","journal-title":"Clin Pharmacol Ther"},{"issue":"2","key":"2024030618341166600_ref10","first-page":"14","article-title":"Introduction to machine learning, neural networks, and deep learning","volume":"9","author":"Choi","year":"2020","journal-title":"Transl Vis Sci Technol"},{"issue":"5","key":"2024030618341166600_ref11","first-page":"851","article-title":"Deep learning in bioinformatics","volume":"18","author":"Min","year":"2017","journal-title":"Brief Bioinform"},{"issue":"9","key":"2024030618341166600_ref12","article-title":"Comparison of conventional statistical methods with machine learning in medicine: diagnosis, drug development, and treatment","volume":"56","author":"Rajula","year":"2020","journal-title":"Medicina (Kaunas)"},{"issue":"1","key":"2024030618341166600_ref13","doi-asserted-by":"crossref","first-page":"12","DOI":"10.11613\/BM.2014.003","article-title":"Understanding logistic regression analysis","volume":"24","author":"Sperandei","year":"2014","journal-title":"Biochem Med (Zagreb)"},{"issue":"Suppl 4","key":"2024030618341166600_ref14","doi-asserted-by":"crossref","first-page":"S574","DOI":"10.21037\/jtd.2019.01.25","article-title":"Developing prediction models for clinical use using logistic regression: an overview","volume":"11","author":"Shipe","year":"2019","journal-title":"J Thorac Dis"},{"issue":"4","key":"2024030618341166600_ref15","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1038\/nmeth.4642","article-title":"Statistics versus machine learning","volume":"15","author":"Bzdok","year":"2018","journal-title":"Nat Methods"},{"issue":"7","key":"2024030618341166600_ref16","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1056\/NEJM197502132920706","article-title":"Polymyositis and dermatomyositis","volume":"292","author":"Bohan","year":"1975","journal-title":"New Engl J Med"},{"issue":"4","key":"2024030618341166600_ref17","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1097\/00005792-197707000-00001","article-title":"A computer-assisted analysis of 153 patients with polymyositis and dermatomyositis","volume":"56","author":"Bohan","year":"1977","journal-title":"Medicine"},{"issue":"5","key":"2024030618341166600_ref18","first-page":"767","article-title":"Classifying idiopathic inflammatory myopathies: comparing the performance of six existing criteria","volume":"31","author":"Linklater","year":"2013","journal-title":"Clin Exp Rheumatol"},{"issue":"6","key":"2024030618341166600_ref19","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1016\/S0002-9343(70)80006-7","article-title":"The epidemiology of polymyositis","volume":"48","author":"Medsger","year":"1970","journal-title":"Am J Med"},{"issue":"4","key":"2024030618341166600_ref20","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1093\/brain\/98.4.637","article-title":"Polymyositis: its presentation, morbidity and mortality","volume":"98","author":"DeVere","year":"1975","journal-title":"Brain"},{"issue":"21","key":"2024030618341166600_ref21","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.1056\/NEJM199111213252107","article-title":"Polymyositis, dermatomyositis and inclusion-body myositis","volume":"325","author":"Dalakas","year":"1991","journal-title":"N Engl J Med"},{"issue":"4","key":"2024030618341166600_ref22","first-page":"668","article-title":"Classification criteria for polymyositis and dermatomyositis","volume":"22","author":"Tanimoto","year":"1995","journal-title":"J Rheumatol"},{"issue":"6","key":"2024030618341166600_ref23","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1097\/00002281-199711000-00008","article-title":"Classification criteria for the idiopathic inflammatory myopathies","volume":"9","author":"Targoff","year":"1997","journal-title":"Curr Opin Rheumatol"},{"issue":"9388","key":"2024030618341166600_ref24","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1016\/S0140-6736(03)14368-1","article-title":"Polymyositis and dermatomyositis","volume":"362","author":"Dalakas","year":"2003","journal-title":"Lancet"},{"issue":"5","key":"2024030618341166600_ref25","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.nmd.2004.02.006","article-title":"119th Enmc international workshop: trial design in adult idiopathic inflammatory myopathies, with the exception of inclusion body myositis, 10-12 October 2003, Naarden, the Netherlands","volume":"14","author":"Hoogendijk","year":"2004","journal-title":"Neuromuscul Disord"},{"issue":"3","key":"2024030618341166600_ref26","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/S0950-3579(05)80255-9","article-title":"Inflammatory myopathies","volume":"9","author":"Oddis","year":"1995","journal-title":"Baillieres Clin Rheumatol"},{"issue":"5","key":"2024030618341166600_ref27","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1002\/ana.410380504","article-title":"Inclusion body myositis and myopathies","volume":"38","author":"Griggs","year":"1995","journal-title":"Ann Neurol"},{"issue":"9","key":"2024030618341166600_ref28","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1212\/WNL.55.9.1385","article-title":"Epidemiology of inclusion body myositis in the Netherlands: a nationwide study","volume":"55","author":"Badrising","year":"2000","journal-title":"Neurology"},{"issue":"4","key":"2024030618341166600_ref29","doi-asserted-by":"crossref","first-page":"e004552","DOI":"10.1136\/bmjopen-2013-004552","article-title":"A retrospective cohort study identifying the principal pathological features useful in the diagnosis of inclusion body myositis","volume":"4","author":"Stefen","year":"2014","journal-title":"BMJ Open"},{"issue":"2","key":"2024030618341166600_ref30","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.nmd.2009.11.003","article-title":"Inclusion body myositis: Mrc Centre for Neuromuscular Diseases, Ibm workshop, London, 13 June 2008","volume":"20","author":"Hilton-Jones","year":"2010","journal-title":"Neuromuscul Disord"},{"issue":"1","key":"2024030618341166600_ref31","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.nmd.2017.09.016","article-title":"224th Enmc international workshop:: Clinico-Sero-pathological classification of immune-mediated necrotizing myopathies Zandvoort, the Netherlands, 14-16 October 2016","volume":"28","author":"Allenbach","year":"2018","journal-title":"Neuromuscul Disord"},{"issue":"12","key":"2024030618341166600_ref32","doi-asserted-by":"crossref","first-page":"1044","DOI":"10.1016\/j.nmd.2013.08.007","article-title":"188th Enmc international workshop: inclusion body myositis, 2-4 December 2011, Naarden, the Netherlands","volume":"23","author":"Rose","year":"2013","journal-title":"Neuromuscul Disord"},{"issue":"2","key":"2024030618341166600_ref33","doi-asserted-by":"crossref","first-page":"109","DOI":"10.3233\/JND-180308","article-title":"Current classification and management of inflammatory myopathies","volume":"5","author":"Schmidt","year":"2018","journal-title":"J Neuromuscul Dis"},{"issue":"1","key":"2024030618341166600_ref34","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1111\/joim.12524","article-title":"Diagnosis and classification of idiopathic inflammatory myopathies","volume":"280","author":"Lundberg","year":"2016","journal-title":"J Intern Med"},{"issue":"3","key":"2024030618341166600_ref35","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1002\/acr2.11115","article-title":"A clinically and biologically based subclassification of the idiopathic inflammatory myopathies using machine learning","volume":"2","author":"Eng","year":"2020","journal-title":"ACR Open Rheumatol"},{"issue":"3","key":"2024030618341166600_ref36","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1093\/rheumatology\/key343","article-title":"The performance of the European league against rheumatism\/American College of Rheumatology Idiopathic Inflammatory Myopathies Classification Criteria in an expert-defined 10 year incident cohort","volume":"58","author":"Parker","year":"2019","journal-title":"Rheumatology (Oxford)"},{"issue":"2","key":"2024030618341166600_ref37","doi-asserted-by":"crossref","first-page":"fcaa191","DOI":"10.1093\/braincomms\/fcaa191","article-title":"Diagnostic modelling and therapeutic monitoring of immune-mediated necrotizing myopathy: role of electrical Myotonia","volume":"2","author":"Triplett","year":"2020","journal-title":"Brain Commun"},{"issue":"5","key":"2024030618341166600_ref38","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1212\/WNL.0000000000000642","article-title":"Evaluation and construction of diagnostic criteria for inclusion body myositis","volume":"83","author":"Lloyd","year":"2014","journal-title":"Neurology"},{"issue":"4","key":"2024030618341166600_ref39","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1097\/01.md.0000173991.74008.b0","article-title":"Novel classification of idiopathic inflammatory myopathies based on overlap syndrome features and autoantibodies: analysis of 100 French Canadian patients","volume":"84","author":"Troyanov","year":"2005","journal-title":"Medicine (Baltimore)"},{"issue":"12","key":"2024030618341166600_ref40","doi-asserted-by":"crossref","first-page":"1528","DOI":"10.1001\/jamaneurol.2018.2598","article-title":"Development of a new classification system for idiopathic inflammatory myopathies based on clinical manifestations and myositis-specific autoantibodies","volume":"75","author":"Mariampillai","year":"2018","journal-title":"JAMA Neurol"},{"issue":"5","key":"2024030618341166600_ref41","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/nrrheum.2018.56","article-title":"Autoantibodies in myositis","volume":"14","author":"McHugh","year":"2018","journal-title":"Nat Rev Rheumatol"},{"issue":"2","key":"2024030618341166600_ref42","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1007\/s40674-021-00174-1","article-title":"Therapeutic management of immune-mediated necrotizing myositis","volume":"7","author":"Weeding","year":"2021","journal-title":"Curr Treatm Opt Rheumatol"},{"issue":"1","key":"2024030618341166600_ref43","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1186\/s13023-020-01431-7","article-title":"Factors associated with refractory autoimmune necrotizing myopathy with anti-signal recognition particle antibodies","volume":"15","author":"Zhao","year":"2020","journal-title":"Orphanet J Rare Dis"},{"issue":"2","key":"2024030618341166600_ref44","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1093\/rheumatology\/keab423","article-title":"Significance of Sj\u00f6gren\u2019s syndrome and anti-Cn1a antibody in myositis patients","volume":"61","author":"Levy","year":"2021","journal-title":"Rheumatology"},{"issue":"2","key":"2024030618341166600_ref45","doi-asserted-by":"crossref","first-page":"384","DOI":"10.55563\/clinexprheumatol\/r625rm","article-title":"Diagnostic and prognostic value of anti-Cn1a antibodies in inclusion body myositis","volume":"40","author":"Salam","year":"2022","journal-title":"Clin Exp Rheumatol"},{"key":"2024030618341166600_ref46","doi-asserted-by":"crossref","first-page":"802499","DOI":"10.3389\/fimmu.2022.802499","article-title":"Machine learning algorithms identify clinical subtypes and cancer in anti-Tif1\u03b3+ myositis: a longitudinal study of 87 patients","volume":"13","author":"Zhao","year":"2022","journal-title":"Front Immunol"},{"issue":"3","key":"2024030618341166600_ref47","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1093\/rheumatology\/keab518","article-title":"Anti-nuclear matrix protein 2 antibody-positive inflammatory myopathies represent extensive myositis without Dermatomyositis-specific rash","volume":"61","author":"Ichimura","year":"2022","journal-title":"Rheumatology (Oxford)"},{"issue":"6","key":"2024030618341166600_ref48","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1097\/BOR.0000000000000641","article-title":"The role of cancer-associated autoantibodies as biomarkers in paraneoplastic myositis syndrome","volume":"31","author":"Lu","year":"2019","journal-title":"Curr Opin Rheumatol"},{"issue":"1","key":"2024030618341166600_ref49","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1186\/s13075-017-1469-8","article-title":"Identification of multiple cancer-associated myositis-specific autoantibodies in idiopathic inflammatory myopathies: a large longitudinal cohort study","volume":"19","author":"Yang","year":"2017","journal-title":"Arthritis Res Ther"},{"issue":"1","key":"2024030618341166600_ref50","doi-asserted-by":"crossref","first-page":"e70","DOI":"10.1212\/WNL.0000000000009727","article-title":"Different phenotypes in Dermatomyositis associated with anti-Mda5 antibody: study of 121 cases","volume":"95","author":"Allenbach","year":"2020","journal-title":"Neurology"},{"issue":"1","key":"2024030618341166600_ref51","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1097\/CND.0000000000000353","article-title":"Diagnostic accuracy of anti-Cn1a on the diagnosis of inclusion body myositis. A hierarchical bivariate and Bayesian meta-analysis","volume":"23","author":"Mavroudis","year":"2021","journal-title":"J Clin Neuromuscul Dis"},{"issue":"1","key":"2024030618341166600_ref52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s43586-020-00001-2","article-title":"Bayesian statistics and modelling","volume":"1","author":"Schoot","year":"2021","journal-title":"Nat Rev Methods Primers"},{"issue":"8","key":"2024030618341166600_ref53","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1016\/j.nmd.2018.06.005","article-title":"Sensitivity and clinical utility of the anti-cytosolic 5'-Nucleotidase 1a (Cn1a) antibody test in sporadic inclusion body myositis: report of 40 patients from a single neuromuscular Center","volume":"28","author":"Felice","year":"2018","journal-title":"Neuromuscul Disord"},{"issue":"4","key":"2024030618341166600_ref54","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1002\/mus.27157","article-title":"Anti-Cn1a antibodies do not correlate with specific clinical, electromyographic, or pathological findings in sporadic inclusion body myositis","volume":"63","author":"Paul","year":"2021","journal-title":"Muscle Nerve"},{"key":"2024030618341166600_ref55","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.3390\/cells10051146","article-title":"Anti-Cn1a antibodies are associated with more severe dysphagia in sporadic inclusion body myositis","volume":"10","author":"Lucchini","year":"2021","journal-title":"Cell"},{"issue":"5","key":"2024030618341166600_ref56","doi-asserted-by":"crossref","first-page":"862","DOI":"10.1136\/annrheumdis-2016-210282","article-title":"Cytosolic 5'-Nucleotidase 1a autoantibody profile and clinical characteristics in inclusion body myositis","volume":"76","author":"Lilleker","year":"2017","journal-title":"Ann Rheum Dis"},{"issue":"1","key":"2024030618341166600_ref57","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1111\/joim.12451","article-title":"Myositis-specific autoantibodies: an important tool to support diagnosis of myositis","volume":"280","author":"Betteridge","year":"2016","journal-title":"J Intern Med"},{"issue":"4","key":"2024030618341166600_ref58","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.autrev.2019.02.003","article-title":"Cd8+(T-bet+) cells as a predominant biomarker for inclusion body myositis","volume":"18","author":"Dzangu\u00e9-Tchoupou","year":"2019","journal-title":"Autoimmun Rev"},{"key":"2024030618341166600_ref59","doi-asserted-by":"crossref","first-page":"756018","DOI":"10.3389\/fimmu.2022.756018","article-title":"High-dimensional analysis reveals distinct Endotypes in patients with idiopathic inflammatory myopathies","volume":"13","author":"Wilfong","year":"2022","journal-title":"Front Immunol"},{"issue":"6","key":"2024030618341166600_ref60","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1038\/nbt.2594","article-title":"Visne enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of Leukemia","volume":"31","author":"E-aD","year":"2013","journal-title":"Nat Biotechnol"},{"issue":"7","key":"2024030618341166600_ref61","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1002\/cyto.a.22625","article-title":"Flowsom: using self-organizing maps for visualization and interpretation of cytometry data","volume":"87","author":"Van Gassen","year":"2015","journal-title":"Cytometry A"},{"issue":"12","key":"2024030618341166600_ref62","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1002\/cyto.a.23030","article-title":"Comparison of clustering methods for high-dimensional single-cell flow and mass cytometry data","volume":"89","author":"Weber","year":"2016","journal-title":"Cytometry A"},{"issue":"8","key":"2024030618341166600_ref63","doi-asserted-by":"crossref","first-page":"3775","DOI":"10.1038\/s41596-021-00550-0","article-title":"Analyzing high-dimensional cytometry data using flowsom","volume":"16","author":"Quintelier","year":"2021","journal-title":"Nat Protoc"},{"issue":"3","key":"2024030618341166600_ref64","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1002\/cyto.a.23917","article-title":"Algorithmic clustering of single-cell cytometry data-how unsupervised are these analyses really?","volume":"97","author":"Pedersen","year":"2020","journal-title":"Cytometry A"},{"issue":"7","key":"2024030618341166600_ref65","doi-asserted-by":"crossref","first-page":"1264","DOI":"10.1038\/nprot.2016.066","article-title":"Visualization and cellular hierarchy inference of single-cell data using Spade","volume":"11","author":"Anchang","year":"2016","journal-title":"Nat Protoc"},{"issue":"11","key":"2024030618341166600_ref66","doi-asserted-by":"crossref","first-page":"1822","DOI":"10.1002\/art.42264","article-title":"Two distinct immune cell signatures predict the clinical outcomes in patients with amyopathic dermatomyositis with interstitial lung disease","volume":"74","author":"Ye","year":"2022","journal-title":"Arthritis Rheumatol"},{"issue":"4","key":"2024030618341166600_ref67","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1111\/joim.13607","article-title":"Peripheral lymphocyte count defines the clinical phenotypes and prognosis in patients with anti-Mda5-positive dermatomyositis","volume":"293","author":"Jin","year":"2023","journal-title":"J Intern Med"},{"key":"2024030618341166600_ref68","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1016\/j.csbj.2023.03.019","article-title":"Identification of feature genes and key biological pathways in immune-Med0iated necrotizing myopathy: high-throughput sequencing and bioinformatics analysis","volume":"21","author":"Chen","year":"2023","journal-title":"Comput Struct Biotechnol J"},{"issue":"9","key":"2024030618341166600_ref69","doi-asserted-by":"crossref","first-page":"1234","DOI":"10.1136\/annrheumdis-2019-216599","article-title":"Machine learning algorithms reveal unique gene expression profiles in muscle biopsies from patients with different types of myositis","volume":"79","author":"Pinal-Fernandez","year":"2020","journal-title":"Ann Rheum Dis"},{"issue":"5","key":"2024030618341166600_ref70","doi-asserted-by":"crossref","first-page":"2456","DOI":"10.1002\/jcsm.13045","article-title":"Integrated analysis of plasma and urine reveals unique Metabolomic profiles in idiopathic inflammatory myopathies subtypes","volume":"13","author":"Liu","year":"2022","journal-title":"J Cachexia Sarcopenia Muscle"},{"issue":"10","key":"2024030618341166600_ref71","doi-asserted-by":"crossref","DOI":"10.3390\/metabo12101004","article-title":"Identification of metabolic signature associated with idiopathic inflammatory myopathy reveals polyamine pathway alteration in muscle tissue","volume":"12","author":"Kang","year":"2022","journal-title":"Metabolites"},{"issue":"10","key":"2024030618341166600_ref72","doi-asserted-by":"crossref","first-page":"1602","DOI":"10.1002\/acn3.51657","article-title":"Metabolome and transcriptome analysis on muscle of sporadic inclusion body myositis","volume":"9","author":"Murakami","year":"2022","journal-title":"Ann Clin Transl Neurol"},{"issue":"2","key":"2024030618341166600_ref73","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.zemedi.2018.11.002","article-title":"An overview of deep learning in medical imaging focusing on Mri","volume":"29","author":"Lundervold","year":"2019","journal-title":"Z Med Phys"},{"issue":"3","key":"2024030618341166600_ref74","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1038\/s41374-021-00647-w","article-title":"Deep convolutional neural network-based algorithm for muscle biopsy diagnosis","volume":"102","author":"Kabeya","year":"2022","journal-title":"Lab Invest"},{"issue":"1","key":"2024030618341166600_ref75","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.chemolab.2004.02.005","article-title":"Image texture analysis: methods and comparisons","volume":"72","author":"Bharati","year":"2004","journal-title":"Chemom Intel Lab Syst"},{"issue":"1","key":"2024030618341166600_ref76","doi-asserted-by":"crossref","first-page":"9821","DOI":"10.1038\/s41598-021-89311-3","article-title":"Texture analysis of muscle Mri: machine learning-based classifications in idiopathic inflammatory myopathies","volume":"11","author":"Nagawa","year":"2021","journal-title":"Sci Rep"},{"key":"2024030618341166600_ref77","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.compbiomed.2018.12.006","article-title":"Deep embeddings for novelty detection in myopathy","volume":"105","author":"Burlina","year":"2019","journal-title":"Comput Biol Med"},{"issue":"7","key":"2024030618341166600_ref78","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.diii.2022.01.012","article-title":"A deep learning tool without muscle-by-muscle grading to differentiate myositis from facio-scapulo-humeral dystrophy using Mri","volume":"103","author":"Fabry","year":"2022","journal-title":"Diagn Interv Imaging"},{"issue":"6","key":"2024030618341166600_ref79","doi-asserted-by":"crossref","first-page":"103105","DOI":"10.1016\/j.autrev.2022.103105","article-title":"A machine learning analysis to predict the response to intravenous and subcutaneous immunoglobulin in inflammatory myopathies. A proposal for a future multi-omics approach in autoimmune diseases","volume":"21","author":"Danieli","year":"2022","journal-title":"Autoimmun Rev"},{"issue":"1","key":"2024030618341166600_ref80","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1186\/s13148-019-0730-1","article-title":"Statistical predictions with Glmnet","volume":"11","author":"Engebretsen","year":"2019","journal-title":"Clin Epigenetics"},{"issue":"6","key":"2024030618341166600_ref81","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.1093\/rheumatology\/keab166","article-title":"A systematic review and meta-analysis to inform cancer screening guidelines in idiopathic inflammatory myopathies","volume":"60","author":"Oldroyd","year":"2021","journal-title":"Rheumatology"},{"key":"2024030618341166600_ref82","first-page":"330","article-title":"Application of logistic regression and machine learning methods for idiopathic inflammatory myopathies malignancy prediction","volume":"41","author":"Zhang","year":"2023","journal-title":"Clin Exp Rheumatol"},{"key":"2024030618341166600_ref83","doi-asserted-by":"crossref","first-page":"224","DOI":"10.55563\/clinexprheumatol\/i2xeao","article-title":"A retrospective cohort study in Chinese patients with adult Polymyositis and Dermatomyositis: risk of comorbidities and subclassification using machine learning","volume":"40","author":"Zhu","year":"2022","journal-title":"Clin Exp Rheumatol"},{"issue":"1","key":"2024030618341166600_ref84","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/s41746-022-00611-y","article-title":"Clinical artificial intelligence quality improvement: towards continual monitoring and updating of Ai algorithms in healthcare","volume":"5","author":"Feng","year":"2022","journal-title":"NPJ Dig Med"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/1\/bbad514\/56843223\/bbad514.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/1\/bbad514\/56843223\/bbad514.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,6]],"date-time":"2024-03-06T18:35:26Z","timestamp":1709750126000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbad514\/7571389"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,22]]},"references-count":84,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,11,22]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbad514","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,1,1]]},"published":{"date-parts":[[2023,11,22]]},"article-number":"bbad514"}}