{"id":"W4362594648","doi":"10.1158/1538-7445.am2023-5440","title":"Abstract 5440: Deep-learning model for tumor type classification enables enhanced clinical decision support in cancer diagnosis","year":2023,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Indel; Cancer; Deep learning; Medicine; Deep sequencing; Classifier (UML); Artificial intelligence; Computational biology; Medical diagnosis; Oncology; Machine learning; Bioinformatics; Genome; Gene; Computer science; Internal medicine; Biology; Genetics; Pathology; Single-nucleotide polymorphism","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001160684,0.0007954441,0.0006655238,0.0006453838,0.0002677982,0.0006535751,0.001107424,0.001065768,0.002514482],"category_scores_gemma":[0.003073848,0.0002993882,0.0008153256,0.0004530097,0.0002608021,0.0007474772,0.0008768009,0.001626818,0.001045229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009315569,"about_ca_system_score_gemma":0.001239223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009658232,"about_ca_topic_score_gemma":0.009699939,"domain_scores_codex":[0.9996182,0.00009183461,0.00002468656,0.0001181249,0.00007598255,0.0000711801],"domain_scores_gemma":[0.9992231,0.0003472473,0.0000584361,0.00007774953,0.0002257275,0.00006765441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000845684,0.0005621492,0.0332455,0.0001356614,0.0002572629,0.000342839,0.0001038321,0.4516852,0.009489177,0.002467773,0.02473257,0.4761324],"study_design_scores_gemma":[0.00001475791,0.00004090882,0.0008309585,0.000009573326,0.00001455438,0.00002764934,0.000005999605,0.9954254,0.001558538,0.00140683,0.0006589393,0.000005975206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4057297,0.002527696,0.5652667,0.004485072,0.0005162809,0.0002572017,0.006581701,0.008798977,0.005836685],"genre_scores_gemma":[0.9184271,0.0003555776,0.07009893,0.0007162822,0.0001122669,0.0001484783,0.005387046,0.00009787938,0.004656534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009658232,"threshold_uncertainty_score":0.01920402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1711863914903168,"score_gpt":0.4840069900520184,"score_spread":0.3128205985617016,"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."}}