{"id":"W4310852955","doi":"10.1038/s41467-022-33407-5","title":"Federated learning enables big data for rare cancer boundary detection","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":340,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke; University of Alberta","funders":"DOD Peer Reviewed Cancer Research Program; CHIST-ERA; FP7 People: Marie-Curie Actions; David Geffen School of Medicine, University of California, Los Angeles; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Medical Research Council; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Whiting School of Engineering, Johns Hopkins University; Anschutz Medical Campus, University of Colorado; Perelman School of Medicine, University of Pennsylvania; Medical Center, University of Pittsburgh; National Institutes of Health; Universitätsklinikum Heidelberg; Lékařská fakulta, Masarykova univerzita; Masarykova Univerzita; Universidade Federal do Paraná; Deutsche Forschungsgemeinschaft; Technische Universität München; NYU Grossman School of Medicine; Case Comprehensive Cancer Center, Case Western Reserve University; Deutsches Krebsforschungszentrum; Fonds National de la Recherche Luxembourg; Engineering and Physical Sciences Research Council; European Commission; Fundação de Amparo à Pesquisa do Estado de São Paulo; Flinders University; Moffitt Cancer Center; National Institute of Mental Health and Neurosciences; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; University of Oxford; Radiological Society of North America; Kepler Universitätsklinikum; University of Bern; Ministerstvo Zdravotnictví Ceské Republiky; Imperial College London; University of Alberta; National Institute of Neurological Disorders and Stroke; Canadian Institute for Advanced Research; Inselspital, Universitätsspital Bern; National Cancer Institute; Alberta Machine Intelligence Institute; KWF Kankerbestrijding; U.S. Department of Defense; Cancer Research UK; Varian Medical Systems; Wellcome Trust; Agenția Națională pentru Cercetare și Dezvoltare; Thomas Jefferson University; School of Medicine, Case Western Reserve University; Washington University in St. Louis; University of Pittsburgh; Johns Hopkins University; Ohio State University; University of Texas MD Anderson Cancer Center; Centre d'Imagerie BioMédicale; Conselho Nacional de Desenvolvimento Científico e Tecnológico; UK Research and Innovation; Deutschen Konsortium für Translationale Krebsforschung; Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute; National Science Foundation; Case Western Reserve University; Chinese University of Hong Kong; Massachusetts General Hospital; University of Pennsylvania; American College of Radiology Imaging Network; University of California, Los Angeles; Intel Corporation; V Foundation for Cancer Research; U.S. National Library of Medicine; Agencia Nacional de Investigación y Desarrollo; Brigham and Women's Hospital","keywords":"Generalizability theory; Computer science; Glioblastoma; Machine learning; Data sharing; Scale (ratio); Sample (material); Task (project management); Data science; Artificial intelligence; Big data; Data mining; Medicine; Psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00597262,0.001236192,0.001434748,0.001414065,0.001109629,0.002364562,0.003364073,0.001784575,0.002398194],"category_scores_gemma":[0.02306846,0.0006304234,0.00133423,0.001671229,0.001288884,0.004311706,0.004540128,0.002664953,0.001617701],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093319,"about_ca_system_score_gemma":0.002342498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00561341,"about_ca_topic_score_gemma":0.008535194,"domain_scores_codex":[0.9965332,0.001327076,0.0001763859,0.001208135,0.0005119505,0.0002433086],"domain_scores_gemma":[0.9908345,0.003204083,0.0005673765,0.003826871,0.00107692,0.0004902771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001321307,0.0009366252,0.04740052,0.000486463,0.0005706333,0.000573304,0.0006432859,0.5187258,0.01024802,0.01343916,0.0311144,0.3745405],"study_design_scores_gemma":[0.00007819555,0.0001483265,0.002984194,0.00003937578,0.00004925729,0.0001401937,0.0002151105,0.9395207,0.00529038,0.04516605,0.006330593,0.00003772771],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1144392,0.001157512,0.8573861,0.002998288,0.0004664953,0.0002636161,0.004262679,0.01538606,0.003640118],"genre_scores_gemma":[0.7550633,0.0002284043,0.2325423,0.0009421917,0.0001717894,0.0003538162,0.008882072,0.000455941,0.001360196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00597262,"threshold_uncertainty_score":0.03158665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07483269328796817,"score_gpt":0.3547455612276453,"score_spread":0.2799128679396771,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). 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