{"id":"W4372267725","doi":"10.1109/icassp49357.2023.10094986","title":"Spatio-Temporal Hybrid Fusion of CAE and SWin Transformers for Lung Cancer Malignancy Prediction","year":2023,"lang":"en","type":"article","venue":"","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre; Concordia University","funders":"","keywords":"Malignancy; Computer science; Lung cancer; Radiology; Artificial intelligence; Transformer; Computed tomography; Medicine; Pathology; Engineering","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":[0.000542598,0.0009670873,0.000831878,0.001458909,0.0001796593,0.0007221045,0.0008840035,0.0006359239,0.0009642857],"category_scores_gemma":[0.001203533,0.0002673225,0.0006898853,0.0007147837,0.0002962682,0.0009230562,0.0006914769,0.0005460063,0.0006158089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004885154,"about_ca_system_score_gemma":0.0006794501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005290315,"about_ca_topic_score_gemma":0.009664916,"domain_scores_codex":[0.9996859,0.00004353281,0.00001636989,0.00009702259,0.00009832367,0.00005891899],"domain_scores_gemma":[0.9996837,0.0001104515,0.00003785064,0.00004630173,0.00009264272,0.00002899877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009518528,0.000450542,0.01973691,0.0001886556,0.0002877351,0.0005465708,0.0000849002,0.1476197,0.05709718,0.003588253,0.005137007,0.7643108],"study_design_scores_gemma":[0.0000156409,0.0001550503,0.003735343,0.00001152741,0.00007390489,0.0004103156,0.00002870271,0.9734407,0.01847855,0.002054307,0.00157733,0.00001861004],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1288386,0.002271684,0.8585413,0.000296588,0.0001000219,0.0001607181,0.001120384,0.005465686,0.003205007],"genre_scores_gemma":[0.8553472,0.0008108158,0.1376716,0.0001811772,0.00006909275,0.0000660978,0.002112522,0.000113217,0.003628369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005290315,"threshold_uncertainty_score":0.01051909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146013172536476,"score_gpt":0.3046252097210669,"score_spread":0.2931650779957022,"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."}}