{"id":"W4401831223","doi":"10.18280/ria.380413","title":"Intelligent Deep Learning System for Enhanced Pulmonary Disease Diagnosis Through Five-Class Mode","year":2024,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mode (computer interface); Class (philosophy); Deep learning; Computer science; Artificial intelligence; Disease; Medicine; Human–computer interaction; Internal medicine","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":[0.0005073113,0.0007476574,0.00067037,0.0007611836,0.0003068393,0.0005570971,0.001316029,0.0007532843,0.003630208],"category_scores_gemma":[0.0007258122,0.0002958073,0.0006574741,0.0003059244,0.0001536258,0.0007152843,0.0008454073,0.0008990029,0.001214332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009565664,"about_ca_system_score_gemma":0.0009959708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008806351,"about_ca_topic_score_gemma":0.01018209,"domain_scores_codex":[0.9998036,0.00001890804,0.00001976721,0.00006809165,0.00005029255,0.0000392813],"domain_scores_gemma":[0.9998032,0.00004103958,0.00001915136,0.000024089,0.00008758734,0.00002479879],"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":[0.0007284121,0.0006070784,0.008420752,0.0002422123,0.0001901959,0.0005218044,0.00008429587,0.09825911,0.02392248,0.002482193,0.029272,0.8352694],"study_design_scores_gemma":[0.00003750401,0.00009920148,0.0009333575,0.00001629496,0.00003110966,0.0001075352,0.000008559343,0.9883218,0.006913001,0.001077555,0.002436432,0.00001747965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1524141,0.002894537,0.7862368,0.00110461,0.0005806976,0.0004648249,0.003245504,0.04541893,0.007639998],"genre_scores_gemma":[0.7469677,0.0008790054,0.2331602,0.0009508372,0.0001334988,0.0004533688,0.006064594,0.000226552,0.01116431],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008806351,"threshold_uncertainty_score":0.01751018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1196188179616074,"score_gpt":0.4322998723721264,"score_spread":0.312681054410519,"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."}}