{"id":"W4313495964","doi":"10.1109/acit57182.2022.9994181","title":"Pancreatic Tumor Detection by Convolutional Neural Networks","year":2022,"lang":"en","type":"article","venue":"2022 International Arab Conference on Information Technology (ACIT)","topic":"AI in cancer detection","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Pancreatic cancer; Convolutional neural network; Artificial intelligence; Computer science; Medical imaging; Cancer; Process (computing); Deep learning; Cancer detection; Computed tomography; Medicine; Radiology; Internal medicine","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":[0.0002348219,0.0006352669,0.0003486034,0.00105993,0.0001722718,0.0005637011,0.0005540702,0.000627186,0.001089535],"category_scores_gemma":[0.0007336131,0.00028831,0.0005253382,0.0006072405,0.0001577946,0.0004418011,0.000425874,0.0005193581,0.0005140148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006471536,"about_ca_system_score_gemma":0.0005442176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01224729,"about_ca_topic_score_gemma":0.01228127,"domain_scores_codex":[0.9998491,0.00001589064,0.000008574255,0.00004386793,0.00004166218,0.00004086454],"domain_scores_gemma":[0.9998585,0.00004010695,0.00002264329,0.00001367355,0.00005196634,0.00001305178],"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":[0.0006005344,0.0003163726,0.01739037,0.0001736039,0.000171646,0.0006731566,0.00006347149,0.194567,0.03722565,0.002002808,0.01199561,0.7348197],"study_design_scores_gemma":[0.00000527403,0.00002085195,0.002034034,0.00001022484,0.00001919126,0.0001025895,0.000009100208,0.9893756,0.006791958,0.0006277773,0.0009960711,0.000007364929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2618794,0.003029321,0.7166032,0.000926078,0.0002327199,0.0001551938,0.00143801,0.006331558,0.009404481],"genre_scores_gemma":[0.8970973,0.001358961,0.0902558,0.0002790759,0.00008899885,0.00007748432,0.001890002,0.000112816,0.008839645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01224729,"threshold_uncertainty_score":0.02435201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007503623571780644,"score_gpt":0.2160305006080841,"score_spread":0.2085268770363034,"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."}}