{"id":"W2570913926","doi":"10.1186/s12880-016-0172-6","title":"Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases","year":2017,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Army Medical Research Acquisition Activity; Congressionally Directed Medical Research Programs; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; DOD Peer Reviewed Cancer Research Program; IXICO; Wallace H. Coulter Foundation; H. Lundbeck A/S; National Cancer Institute; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; National Science Foundation; Case Western Reserve University; Bristol-Myers Squibb; Cleveland Clinic; F. Hoffmann-La Roche; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Foundation for the National Institutes of Health; Case Comprehensive Cancer Center, Case Western Reserve University; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Computer science; Workflow; Context (archaeology); Dimensionality reduction; Sensor fusion; Artificial intelligence; Identification (biology); Data mining; Data integration; Machine learning; Modalities; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02296297,0.001452486,0.001080389,0.007993544,0.0009992055,0.005095973,0.002075403,0.001693651,0.001212162],"category_scores_gemma":[0.02671708,0.0005939195,0.002505134,0.007979837,0.00278024,0.005079249,0.004239755,0.002155547,0.0007133822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002030375,"about_ca_system_score_gemma":0.00217244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001724785,"about_ca_topic_score_gemma":0.001404186,"domain_scores_codex":[0.9845781,0.006319946,0.001766132,0.001596495,0.00537589,0.0003635015],"domain_scores_gemma":[0.9762397,0.0130247,0.002758979,0.003510784,0.004001221,0.0004645926],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003203755,0.0004337819,0.02255231,0.002984423,0.0006067874,0.0007479317,0.003105228,0.06454958,0.01384158,0.1049248,0.008245968,0.7776871],"study_design_scores_gemma":[0.00008576189,0.0006680851,0.02061709,0.001904622,0.0003593068,0.00354614,0.002508121,0.5422447,0.05474335,0.3117596,0.06112571,0.0004376613],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02021793,0.005718856,0.9660898,0.002614798,0.00006644252,0.000418048,0.000542529,0.001016474,0.003315026],"genre_scores_gemma":[0.1542474,0.004415981,0.839015,0.0002341506,0.00009713733,0.0005595107,0.0008881459,0.0001285153,0.000414112],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02296297,"threshold_uncertainty_score":0.1214412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07334934955420616,"score_gpt":0.3632264358934835,"score_spread":0.2898770863392773,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}