{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T18:14:35Z","timestamp":1790014475107,"version":"4.0.1"},"reference-count":75,"publisher":"Elsevier BV","issue":"9","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100004901","name":"Minas Gerais State Foundation of Support to the Research","doi-asserted-by":"publisher","award":["APQ-04185-10"],"award-info":[{"award-number":["APQ-04185-10"]}],"id":[{"id":"10.13039\/501100004901","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002322","name":"Coordination of Higher Education Personnel Improvement","doi-asserted-by":"publisher","award":["88881.068041\/2014-01"],"award-info":[{"award-number":["88881.068041\/2014-01"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["456080\/2014-7"],"award-info":[{"award-number":["456080\/2014-7"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["MCTIC N\\u00BA28\/2018"],"award-info":[{"award-number":["MCTIC N\\u00BA28\/2018"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100016062","name":"National Health Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100016062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006506","name":"Minist\u00e9rio da Sa\u00fade","doi-asserted-by":"publisher","award":["25000.155761\/2015-13"],"award-info":[{"award-number":["25000.155761\/2015-13"]}],"id":[{"id":"10.13039\/501100006506","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["jthjournal.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Thrombosis and Haemostasis"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1016\/j.jtha.2024.05.017","type":"journal-article","created":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T12:36:34Z","timestamp":1716813394000},"page":"2426-2437","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":10,"title":["Prediction of inhibitor development in previously untreated and minimally treated children with severe and moderately severe hemophilia A using a machine-learning network"],"prefix":"10.1016","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3358-0075","authenticated-orcid":false,"given":"Let\u00edcia Lemos","family":"Jardim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiago A.","family":"Schieber","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcio Portugal","family":"Santana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00f4nica Hermida","family":"Cerqueira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia Santos","family":"Lorenzato","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vivian Karla Brognoli","family":"Franco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luciana Werneck","family":"Zuccherato","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brendon Ayala","family":"da Silva Santos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel Gon\u00e7alves","family":"Chaves","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mart\u00edn Gomez","family":"Ravetti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suely Meireles","family":"Rezende","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jtha.2024.05.017_bib1","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1002\/rth2.12335","article-title":"Development of inhibitors in hemophilia A: an illustrated review","volume":"4","author":"Jardim","year":"2020","journal-title":"Res Pract Thromb Haemost"},{"key":"10.1016\/j.jtha.2024.05.017_bib2","first-page":"1379","article-title":"Accelerating approximate inference with non-uniform probability density trees","volume":"11","author":"Carreira-Perpi\u00f1\u00e1n","year":"2010","journal-title":"J\u00a0Mach Learn Res"},{"key":"10.1016\/j.jtha.2024.05.017_bib3","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1002\/jcc.21707","article-title":"PaDEL-descriptor: an open source software to calculate molecular descriptors and fingerprints","volume":"32","author":"Yap","year":"2011","journal-title":"J\u00a0Comput Chem"},{"key":"10.1016\/j.jtha.2024.05.017_bib4","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1038\/nrg3920","article-title":"Machine learning applications in genetics and genomics","volume":"16","author":"Libbrecht","year":"2015","journal-title":"Nat Rev Genet"},{"key":"10.1016\/j.jtha.2024.05.017_bib5","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/nature21056","article-title":"Dermatologist-level classification of skin cancer with deep neural networks","volume":"542","author":"Esteva","year":"2017","journal-title":"Nature"},{"key":"10.1016\/j.jtha.2024.05.017_bib6","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1002\/jcc.24764","article-title":"Deep learning for computational chemistry","volume":"38","author":"Goh","year":"2017","journal-title":"J\u00a0Comput Chem"},{"key":"10.1016\/j.jtha.2024.05.017_bib7","doi-asserted-by":"crossref","unstructured":"Huang G, Liu Z, Van Der Maaten L, Weinberger KQ. Densely connected convolutional networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, Honolulu; 21-26 Jul 2017. p. 2261-9.","DOI":"10.1109\/CVPR.2017.243"},{"key":"10.1016\/j.jtha.2024.05.017_bib8","doi-asserted-by":"crossref","DOI":"10.1098\/rsif.2017.0387","article-title":"Opportunities and obstacles for deep learning in biology and medicine","volume":"15","author":"Ching","year":"2018","journal-title":"J\u00a0R Soc Interface"},{"key":"10.1016\/j.jtha.2024.05.017_bib9","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1038\/s41591-018-0316-z","article-title":"A\u00a0guide to deep learning in healthcare","volume":"25","author":"Esteva","year":"2019","journal-title":"Nat Med"},{"key":"10.1016\/j.jtha.2024.05.017_bib10","doi-asserted-by":"crossref","first-page":"7997","DOI":"10.1007\/s00432-023-04667-5","article-title":"An overview and a roadmap for artificial intelligence in hematology and oncology","volume":"149","author":"R\u00f6sler","year":"2023","journal-title":"J\u00a0Cancer Res Clin Oncol"},{"key":"10.1016\/j.jtha.2024.05.017_bib11","doi-asserted-by":"crossref","first-page":"797","DOI":"10.3390\/cancers12040797","article-title":"Artificial intelligence and digital microscopy applications in diagnostic hematopathology","volume":"12","author":"El Achi","year":"2020","journal-title":"Cancers"},{"key":"10.1016\/j.jtha.2024.05.017_bib12","doi-asserted-by":"crossref","first-page":"264","DOI":"10.3389\/fmed.2019.00264","article-title":"Deep learning for whole slide image analysis: an overview","volume":"6","author":"Dimitriou","year":"2019","journal-title":"Front Med"},{"key":"10.1016\/j.jtha.2024.05.017_bib13","doi-asserted-by":"crossref","DOI":"10.1038\/srep14938","article-title":"An intelligent decision support system for leukaemia diagnosis using microscopic blood images","volume":"5","author":"Chin Neoh","year":"2015","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib14","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1182\/bloodadvances.2020002230","article-title":"Artificial intelligence-based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients","volume":"4","author":"Sirinukunwattana","year":"2020","journal-title":"Blood Adv"},{"key":"10.1016\/j.jtha.2024.05.017_bib15","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1136\/jclinpath-2019-205949","article-title":"Automatic recognition of different types of acute leukaemia in peripheral blood by image analysis","volume":"72","author":"Bold\u00fa","year":"2019","journal-title":"J\u00a0Clin Pathol"},{"key":"10.1016\/j.jtha.2024.05.017_bib16","series-title":"2010 International Conference on Digital Image Computing: Techniques and Applications","first-page":"605","article-title":"Chromosome classification based on wavelet neural network","author":"Oskouei","year":"2010"},{"key":"10.1016\/j.jtha.2024.05.017_bib17","series-title":"IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)","first-page":"626","article-title":"Human chromosome classification using Competitive Neural Network Teams (CNNT) and Nearest Neighbor","author":"Gagula-Palalic","year":"2014"},{"key":"10.1016\/j.jtha.2024.05.017_bib18","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1182\/blood-2020-137463","article-title":"Artificial intelligence substantially supports chromosome banding analysis maintaining its strengths in hematologic diagnostics even in the era of newer technologies","volume":"136","author":"Haferlach","year":"2020","journal-title":"Blood"},{"key":"10.1016\/j.jtha.2024.05.017_bib19","doi-asserted-by":"crossref","first-page":"10725","DOI":"10.1182\/blood-2022-168780","article-title":"A\u00a0fully automated digital workflow for assessment of bone marrow cytomorphology based on single cell detection and classification with AI","volume":"140","author":"Pohlkamp","year":"2022","journal-title":"Blood"},{"key":"10.1016\/j.jtha.2024.05.017_bib20","doi-asserted-by":"crossref","first-page":"1073","DOI":"10.1002\/cyto.a.24159","article-title":"Hematologist-level classification of mature B-cell neoplasm using deep learning on multiparameter flow cytometry data","volume":"97","author":"Zhao","year":"2020","journal-title":"Cytom A"},{"key":"10.1016\/j.jtha.2024.05.017_bib21","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1097\/CCO.0000000000000607","article-title":"Computational analysis of flow cytometry data in hematological malignancies: future clinical practice?","volume":"32","author":"Duetz","year":"2020","journal-title":"Curr Opin Oncol"},{"key":"10.1016\/j.jtha.2024.05.017_bib22","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0072932","article-title":"Leukemi a prediction using sparse logistic regression","volume":"8","author":"Manninen","year":"2013","journal-title":"PLoS One"},{"key":"10.1016\/j.jtha.2024.05.017_bib23","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1111\/bjh.15230","article-title":"Machine learning algorithms for accurate differential diagnosis of lymphocytosis based on cell population data","volume":"184","author":"Bigorra","year":"2019","journal-title":"Br J Haematol"},{"key":"10.1016\/j.jtha.2024.05.017_bib24","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.ebiom.2018.10.042","article-title":"Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome","volume":"37","author":"Ko","year":"2018","journal-title":"EBioMedicine"},{"key":"10.1016\/j.jtha.2024.05.017_bib25","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1038\/s41588-018-0295-5","article-title":"A\u00a0primer on deep learning in genomics","volume":"51","author":"Zou","year":"2019","journal-title":"Nat Genet"},{"key":"10.1016\/j.jtha.2024.05.017_bib26","doi-asserted-by":"crossref","first-page":"5122","DOI":"10.1016\/j.ygeno.2020.09.020","article-title":"Machine learning method using position-specific mutation based classification outperforms one hot coding for disease severity prediction in haemophilia \u2018A","volume":"112","author":"Singh","year":"2020","journal-title":"Genomics"},{"key":"10.1016\/j.jtha.2024.05.017_bib27","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1038\/s41540-021-00183-9","article-title":"Prediction of hemophilia A severity using a small-input machine-learning framework","volume":"7","author":"Lopes","year":"2021","journal-title":"NPJ Syst Biol Appl"},{"key":"10.1016\/j.jtha.2024.05.017_bib28","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1080\/17474086.2022.2114895","article-title":"The current role of artificial intelligence in hemophilia","volume":"15","author":"Rodriguez-Merchan","year":"2022","journal-title":"Expert Rev Hematol"},{"key":"10.1016\/j.jtha.2024.05.017_bib29","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of 'small-world' networks","volume":"393","author":"Watts","year":"1998","journal-title":"Nature"},{"key":"10.1016\/j.jtha.2024.05.017_bib30","doi-asserted-by":"crossref","first-page":"7821","DOI":"10.1073\/pnas.122653799","article-title":"Community structure in social and biological networks","volume":"99","author":"Girvan","year":"2002","journal-title":"Proc Natl Acad Sci U S A"},{"key":"10.1016\/j.jtha.2024.05.017_bib31","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1137\/S003614450342480","article-title":"The structure and function of complex networks","volume":"45","author":"Newman","year":"2003","journal-title":"SIAM Rev"},{"key":"10.1016\/j.jtha.2024.05.017_bib32","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1007\/s10618-012-0295-5","article-title":"Training and assessing classification rules with imbalanced data","volume":"28","author":"Menardi","year":"2014","journal-title":"Data Min Knowl Discov"},{"key":"10.1016\/j.jtha.2024.05.017_bib33","doi-asserted-by":"crossref","DOI":"10.2202\/1544-6115.1128","article-title":"A\u00a0general framework for weighted gene co-expression network analysis","volume":"4","author":"Zhang","year":"2005","journal-title":"Stat Appl Genet Mol Biol"},{"key":"10.1016\/j.jtha.2024.05.017_bib34","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1038\/nbt.1567","article-title":"How to visually interpret biological data using networks","volume":"27","author":"Merico","year":"2009","journal-title":"Nat Biotechnol"},{"issue":"3","key":"10.1016\/j.jtha.2024.05.017_bib35","first-page":"52","article-title":"Representation learning on graphs: Methods and applications","volume":"40","author":"Hamilton","year":"2017","journal-title":"IEEE Data Engineering Bulletin"},{"key":"10.1016\/j.jtha.2024.05.017_bib36","doi-asserted-by":"crossref","first-page":"6794","DOI":"10.1038\/s41467-022-34267-9","article-title":"Statistical inference links data and theory in network science","volume":"13","author":"Peel","year":"2022","journal-title":"Nat Commun"},{"key":"10.1016\/j.jtha.2024.05.017_bib37","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1038\/s41598-022-19827-9","article-title":"New approaches to epidemic modeling on networks","volume":"13","author":"G\u00f3mez","year":"2023","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib38","doi-asserted-by":"crossref","first-page":"4511","DOI":"10.1038\/s41598-019-38869-0","article-title":"Assessing diversity in multiplex networks","volume":"9","author":"Carpi","year":"2019","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib39","doi-asserted-by":"crossref","first-page":"2217","DOI":"10.1038\/s41467-023-37323-0","article-title":"Diffusion capacity of single and interconnected networks","volume":"14","author":"Schieber","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.jtha.2024.05.017_bib40","doi-asserted-by":"crossref","DOI":"10.1038\/ncomms13928","article-title":"Quantification of network structural dissimilarities","volume":"8","author":"Schieber","year":"2017","journal-title":"Nat Commun"},{"key":"10.1016\/j.jtha.2024.05.017_bib41","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1097\/MBC.0000000000001057","article-title":"Risk factors for antibody formation in children with hemophilia: methodological aspects and clinical characteristics of the HEMFIL cohort study","volume":"32","author":"Jardim","year":"2021","journal-title":"Blood Coagul Fibrinolysis"},{"key":"10.1016\/j.jtha.2024.05.017_bib42","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1111\/bjh.14799","article-title":"Immune status\u00a0of patients with haemophilia A before exposure to factor VIII: first results from the HEMFIL study","volume":"178","author":"Jardim","year":"2017","journal-title":"Br J Haematol"},{"key":"10.1016\/j.jtha.2024.05.017_bib43","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1055\/s-0037-1615621","article-title":"Factor VIII and Factor IX Subcommittee. Definitions in hemophilia. Recommendation of the scientific subcommittee on factor VIII and factor IX of the scientific and standardization committee of the International Society on Thrombosis and Haemostasis","volume":"85","author":"White","year":"2001","journal-title":"Thromb Haemost"},{"key":"10.1016\/j.jtha.2024.05.017_bib44","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1111\/j.1365-2516.2010.02392.x","article-title":"Detection of int1h-related inversion of the factor VIII gene","volume":"17","author":"Pio","year":"2011","journal-title":"Haemophilia"},{"key":"10.1016\/j.jtha.2024.05.017_bib45","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1111\/j.1538-7836.2008.02926.x","article-title":"Developing a new generation of tests for genotyping hemophilia-causative rearrangements involving int22h and int1h hotspots in the factor VIII gene","volume":"6","author":"Rossetti","year":"2008","journal-title":"J\u00a0Thromb Haemost"},{"key":"10.1016\/j.jtha.2024.05.017_bib46","doi-asserted-by":"crossref","first-page":"1757","DOI":"10.1182\/blood-2017-06-791756","article-title":"Genetic risk stratification to reduce inhibitor development in the early treatment of hemophilia A: a SIPPET analysis","volume":"130","author":"Rosendaal","year":"2017","journal-title":"Blood"},{"key":"10.1016\/j.jtha.2024.05.017_bib47","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.thromres.2018.05.027","article-title":"Risk factors for inhibitor development in severe hemophilia A","volume":"168","author":"Garagiola","year":"2018","journal-title":"Thromb Res"},{"key":"10.1016\/j.jtha.2024.05.017_bib48","article-title":"Weight thresholding on complex networks","volume":"E 98","author":"Yan","year":"2018","journal-title":"Phys. Rev"},{"key":"10.1016\/j.jtha.2024.05.017_bib49","doi-asserted-by":"crossref","first-page":"3094","DOI":"10.1038\/s41598-018-21261-9","article-title":"Threshold driven contagion on weighted networks","volume":"8","author":"Unicomb","year":"2018","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib50","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-022-22079-2","article-title":"The thresholding problem and variability in the EEG graph network parameters","volume":"12","author":"Adamovich","year":"2022","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib51","article-title":"Fast unfolding of communities in large networks","volume":"12","author":"Blondel","year":"2008","journal-title":"J\u00a0Stat Mech"},{"key":"10.1016\/j.jtha.2024.05.017_bib52","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0011976","article-title":"Characterizing the community structure of complex networks","volume":"5","author":"Lancichinetti","year":"2010","journal-title":"PLoS One"},{"key":"10.1016\/j.jtha.2024.05.017_bib53","article-title":"A\u00a0Comparative analysis of community detection algorithms on artificial networks","volume":"6","author":"Yang","year":"2016","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib54","doi-asserted-by":"crossref","first-page":"5623","DOI":"10.1038\/s41598-021-84838-x","article-title":"Visibility graph based temporal community detection with applications in biological time series","volume":"11","author":"Zheng","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib55","doi-asserted-by":"crossref","first-page":"5233","DOI":"10.1038\/s41598-019-41695-z","article-title":"From Louvain to Leiden: guaranteeing well-connected communities","volume":"9","author":"Traag","year":"2019","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib56","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1080\/01621459.1993.10476299","article-title":"Linear model selection by cross-validation","volume":"88","author":"Shao","year":"1993","journal-title":"J\u00a0Am Stat Assoc"},{"key":"10.1016\/j.jtha.2024.05.017_bib57","first-page":"1137","article-title":"A\u00a0study of cross-validation and bootstrap for accuracy estimation and model selection","volume":"2","author":"Kohavi","year":"1995","journal-title":"In: Proceedings of the 14th international joint conference on Artificial intelligence"},{"key":"10.1016\/j.jtha.2024.05.017_bib58","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1186\/1471-2105-7-91","article-title":"Bias in error estimation when using cross-validation for model selection","volume":"7","author":"Varma","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"10.1016\/j.jtha.2024.05.017_bib59","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1214\/09-SS054","article-title":"A\u00a0survey of cross-validation procedures for model selection","volume":"4","author":"Arlot","year":"2010","journal-title":"Stat Surv"},{"key":"10.1016\/j.jtha.2024.05.017_bib60","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1038\/nature10011","article-title":"Controllability of complex networks","volume":"473","author":"Liu","year":"2011","journal-title":"Nature"},{"key":"10.1016\/j.jtha.2024.05.017_bib61","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1038\/nrg3383","article-title":"Robustness and plasticity in network evolution","volume":"13","author":"Flintoft","year":"2012","journal-title":"Nat Rev Genet"},{"key":"10.1016\/j.jtha.2024.05.017_bib62","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-44914-2_5","article-title":"A\u00a0review on network robustness from an information theory perspective","volume":"9869","author":"Schieber","year":"2016","journal-title":"Lect Notes Comput Sci Discrete Optimization and Operations Research DOOR"},{"key":"10.1016\/j.jtha.2024.05.017_bib63","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.physleta.2015.10.055","article-title":"Information theory perspective on network robustness","volume":"380","author":"Schieber","year":"2016","journal-title":"Phys Lett A"},{"key":"10.1016\/j.jtha.2024.05.017_bib64","doi-asserted-by":"crossref","first-page":"8567","DOI":"10.1038\/s41598-017-08714-3","article-title":"Network robustness assessed within a dual connectivity framework: joint dynamics of the Active and Idle Networks","volume":"7","author":"Tejedor","year":"2017","journal-title":"Sci Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib65","first-page":"1","article-title":"Robustness of networks under attack and defense strategies: state of the art and challenges","volume":"816","author":"Zhao","year":"2019","journal-title":"Phys Rep"},{"key":"10.1016\/j.jtha.2024.05.017_bib66","doi-asserted-by":"crossref","first-page":"6043","DOI":"10.1038\/s41467-020-19841-3","article-title":"Robustness and lethality in multilayer biological molecular networks","volume":"11","author":"Liu","year":"2020","journal-title":"Nat Commun"},{"key":"10.1016\/j.jtha.2024.05.017_bib67","doi-asserted-by":"crossref","first-page":"1033","DOI":"10.1038\/s41567-023-02020-8","article-title":"Emergent stability in complex network dynamics","volume":"19","author":"Meena","year":"2023","journal-title":"Nat Phys"},{"key":"10.1016\/j.jtha.2024.05.017_bib68","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1111\/jth.13961","article-title":"Prediction of factor VIII inhibitor development in the SIPPET cohort by mutational analysis and factor VIII antigen measurement","volume":"16","author":"Spena","year":"2018","journal-title":"J\u00a0Thromb Haemost"},{"key":"10.1016\/j.jtha.2024.05.017_bib69","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1182\/bloodadvances.2022007267","article-title":"Prospective Hemophilia Inhibitor PUP Study reveals distinct antibody signatures during FVIII inhibitor eradication","volume":"7","author":"Paul","year":"2023","journal-title":"Blood Adv"},{"key":"10.1016\/j.jtha.2024.05.017_bib70","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1038\/s43856-023-00356-z","article-title":"The impact of imputation quality on machine learning classifiers for datasets with missing values","volume":"3","author":"Shadbahr","year":"2023","journal-title":"Commun Med (Lond)"},{"key":"10.1016\/j.jtha.2024.05.017_bib71","doi-asserted-by":"crossref","first-page":"55","DOI":"10.3390\/bdcc7010055","article-title":"Effect of missing data types and imputation methods on supervised classifiers: an evaluation study","volume":"7","author":"Gabr","year":"2023","journal-title":"Big Data Cogn Comput"},{"key":"10.1016\/j.jtha.2024.05.017_bib72","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1111\/j.1365-2249.2010.04258.x","article-title":"A\u00a0shift towards a T cell cytokine deficiency along with an anti-inflammatory\/regulatory microenvironment may enable the synthesis of anti-FVIII inhibitors in haemophilia A patients","volume":"162","author":"Chaves","year":"2010","journal-title":"Clin Exp Immunol"},{"key":"10.1016\/j.jtha.2024.05.017_bib73","doi-asserted-by":"crossref","first-page":"e139","DOI":"10.1111\/hae.12096","article-title":"Cytokine profile and FVIII inhibitors development in haemophilia A","volume":"19","author":"Oliveira","year":"2013","journal-title":"Haemophilia"},{"key":"10.1016\/j.jtha.2024.05.017_bib74","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1182\/blood-2016-06-720086","article-title":"Nonneutralizing antibodies against factor VIII and risk of inhibitor development in severe hemophilia A","volume":"129","author":"Cannav\u00f2","year":"2017","journal-title":"Blood"},{"key":"10.1016\/j.jtha.2024.05.017_bib75","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1055\/s-0040-1722353","article-title":"Effect of the first factor VIII infusions on immunological biomarkers in previously untreated patients with hemophilia A from the HEMFIL study","volume":"121","author":"de Oliveira","year":"2021","journal-title":"Thromb Haemost"}],"container-title":["Journal of Thrombosis and Haemostasis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1538783624003039?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1538783624003039?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T20:27:12Z","timestamp":1778617632000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1538783624003039"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":75,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["S1538783624003039"],"URL":"https:\/\/doi.org\/10.1016\/j.jtha.2024.05.017","relation":{},"ISSN":["1538-7836"],"issn-type":[{"value":"1538-7836","type":"print"}],"subject":[],"published":{"date-parts":[[2024,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Prediction of inhibitor development in previously untreated and minimally treated children with severe and moderately severe hemophilia A using a machine-learning network","name":"articletitle","label":"Article Title"},{"value":"Journal of Thrombosis and Haemostasis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jtha.2024.05.017","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 International Society on Thrombosis and Haemostasis. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}]}}