{"id":"W4408793525","doi":"10.1109/raaicon64172.2024.10928428","title":"Lung Cancer Prediction and Risk Assessment: A Machine Learning Approach Integrating Symptoms and Etiological Factors","year":2024,"lang":"en","type":"article","venue":"","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Cancer Research","keywords":"Etiology; Computer science; Lung cancer; Cancer; Artificial intelligence; Machine learning; Risk analysis (engineering); Medicine; Oncology; Internal medicine","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":[0.003625783,0.0007429049,0.00107936,0.003298027,0.0003910972,0.001606995,0.0009612715,0.0008541743,0.001264977],"category_scores_gemma":[0.009509784,0.0003121587,0.0008298992,0.001903093,0.0003522687,0.001184707,0.0007903734,0.001542328,0.0004106121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007623665,"about_ca_system_score_gemma":0.001309587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004297878,"about_ca_topic_score_gemma":0.004610277,"domain_scores_codex":[0.99829,0.0009430486,0.0001681321,0.0002527954,0.0002723402,0.00007375811],"domain_scores_gemma":[0.996837,0.002255072,0.0003333158,0.000132331,0.0003130675,0.000129166],"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":[0.00049144,0.00127204,0.3166508,0.0005718853,0.000642129,0.0003185292,0.00043451,0.1198096,0.00373048,0.00729345,0.006695105,0.5420901],"study_design_scores_gemma":[0.0000901196,0.0008650887,0.1136672,0.0003500911,0.0002840694,0.0008211373,0.0005785854,0.8240491,0.003894374,0.04636449,0.008887147,0.0001486056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2051118,0.005202347,0.7737096,0.005488928,0.0001729514,0.0006995057,0.002464084,0.00102396,0.006126876],"genre_scores_gemma":[0.7676749,0.001419834,0.2277097,0.0003811434,0.0002369917,0.0002929573,0.001032296,0.00003475642,0.001217454],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004297878,"threshold_uncertainty_score":0.01917517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009283514437527507,"score_gpt":0.3100088446125018,"score_spread":0.3007253301749743,"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."}}