{"id":"W4323657894","doi":"10.18280/isi.280125","title":"Prediction of Lungs Cancer in Medical Images Using Deep Learning Approach","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deep learning; Artificial intelligence; Cancer; Lung cancer; Computer science; Medicine; Medical physics; Pathology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001090193,0.0001231004,0.000296903,0.000549574,0.0001003616,0.0000335751,0.00009392463,0.0001436763,0.00008726088],"category_scores_gemma":[0.001294552,0.0001119066,0.00006415042,0.0008536524,0.0001687615,0.0006926389,0.00005765348,0.0004722843,0.00001106065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002269777,"about_ca_system_score_gemma":0.0001600895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000427893,"about_ca_topic_score_gemma":0.00000303154,"domain_scores_codex":[0.9983358,0.00006852728,0.0006359325,0.0001182319,0.0005645762,0.0002768861],"domain_scores_gemma":[0.9993377,0.00006338231,0.0002219473,0.0001146483,0.0001365648,0.0001257754],"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":[0.0001487408,0.00008406818,0.378734,0.003138791,0.000125267,0.00003518789,0.01446417,0.06742501,0.004152948,0.0004315531,0.0004936559,0.5307666],"study_design_scores_gemma":[0.0009329052,0.00005241734,0.1127974,0.0006933999,0.00003359847,0.00009512922,0.001048414,0.8832195,0.0002850874,0.0001263531,0.000627649,0.00008812985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9452947,0.0002338562,0.04791617,0.0002002046,0.0002634274,0.0003028337,0.00001097034,0.0002076417,0.00557019],"genre_scores_gemma":[0.9970427,0.0003431953,0.002120588,0.0001115973,0.0001136348,0.00003214468,0.0001511202,0.00001677186,0.0000682059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8157945,"threshold_uncertainty_score":0.4563418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808663912172054,"score_gpt":0.2852631100678545,"score_spread":0.267176470946134,"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."}}