{"id":"W4309655877","doi":"10.1093/bfgp/elac038","title":"Deep learning-based classifier of diffuse large B-cell lymphoma cell-of-origin with clinical outcome","year":2022,"lang":"en","type":"article","venue":"Briefings in Functional Genomics","topic":"Lymphoma Diagnosis and Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"BC Cancer Agency; Ministry of Education, India; Council of Scientific and Industrial Research, India","keywords":"Diffuse large B-cell lymphoma; Classifier (UML); Artificial intelligence; Machine learning; CHOP; Multilayer perceptron; Lymphoma; Oncology; Perceptron; Overall survival; Internal medicine; Computer science; Medicine; Artificial neural network","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":[0.0009804051,0.0005636491,0.0006163198,0.0008731484,0.0001668463,0.0004283836,0.000533251,0.0006136517,0.0006715059],"category_scores_gemma":[0.002008389,0.0001256923,0.0004363739,0.0004211224,0.0001718817,0.0002951237,0.0005027484,0.0007242879,0.0002722558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005867628,"about_ca_system_score_gemma":0.000611135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004912361,"about_ca_topic_score_gemma":0.004425195,"domain_scores_codex":[0.9996276,0.0000708896,0.00003356748,0.00009320449,0.00007350818,0.0001011696],"domain_scores_gemma":[0.9993849,0.0002205569,0.00007672552,0.00004155889,0.0001966538,0.00007961796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001289652,0.001017788,0.5079086,0.0001713549,0.000388649,0.001088652,0.0002003477,0.1937883,0.01740268,0.0006460703,0.01213731,0.2639605],"study_design_scores_gemma":[0.00003533041,0.0001872025,0.03827334,0.00002018914,0.00007076456,0.0001673845,0.00004913447,0.9550918,0.004589716,0.0007089635,0.0007851981,0.00002088416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653521,0.0007770848,0.02986007,0.0005078695,0.00007377853,0.00006810662,0.001633956,0.0004826566,0.00124448],"genre_scores_gemma":[0.9936637,0.00009074577,0.003888301,0.00009542298,0.00001723675,0.00004582154,0.001574212,0.000008708956,0.0006158701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004912361,"threshold_uncertainty_score":0.009767532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03483489723150836,"score_gpt":0.2775315387444447,"score_spread":0.2426966415129364,"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."}}