{"id":"W3170419072","doi":"10.2196/27955","title":"Automatic Extraction of Lung Cancer Staging Information From Computed Tomography Reports: Deep Learning Approach","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lung cancer; Medicine; Computed tomography; Radiology; Cancer; Lung cancer staging; Modalities; Pathological; Clinical Practice; Cancer staging; Medical physics; Oncology; Pathology; Internal medicine; Physical therapy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.00100058,0.001635651,0.001006381,0.004514903,0.0004230384,0.001044111,0.001478537,0.001181431,0.00124466],"category_scores_gemma":[0.002646404,0.0004428973,0.001493732,0.002810736,0.0003014716,0.001324243,0.0009761829,0.001061241,0.001070657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007621243,"about_ca_system_score_gemma":0.001248098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007910554,"about_ca_topic_score_gemma":0.007823269,"domain_scores_codex":[0.9991742,0.0001176399,0.0001521473,0.0002793413,0.0001773307,0.00009939582],"domain_scores_gemma":[0.9987528,0.0005584097,0.0001903598,0.0001372176,0.0003128401,0.00004820936],"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":[0.0003613483,0.0005235567,0.01506984,0.0005469386,0.0001937899,0.0006546225,0.0002303497,0.04018258,0.02280165,0.0007821905,0.01239823,0.9062548],"study_design_scores_gemma":[0.00004833315,0.0002117541,0.01071967,0.0001055149,0.0002404765,0.000482218,0.0001690752,0.9516134,0.02690005,0.002938689,0.006520111,0.00005076519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2002042,0.005209228,0.7607285,0.001256161,0.0002628411,0.0007709956,0.00896387,0.01924176,0.003362474],"genre_scores_gemma":[0.502351,0.002154675,0.4648601,0.000401805,0.0001767221,0.0004575822,0.02579144,0.0001569486,0.003649883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007910554,"threshold_uncertainty_score":0.01572901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009387121173403021,"score_gpt":0.3046130268829353,"score_spread":0.2952259057095323,"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."}}