{"id":"W4412378850","doi":"10.1002/aisy.202500282","title":"Optimized DeepLabV3+ for Clinical Data Analysis through Advanced Particle Swarm Optimization‐Based Channel Selection","year":2025,"lang":"en","type":"article","venue":"Advanced Intelligent Systems","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; York University; Ontario Centre of Innovation","keywords":"Particle swarm optimization; Selection (genetic algorithm); Computer science; Channel (broadcasting); Mathematical optimization; Psychology; Statistics; Artificial intelligence; Algorithm; Mathematics; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001118185,0.0003614956,0.00117206,0.0003441688,0.0002487889,0.00008312287,0.0004633256,0.000218597,0.00005007656],"category_scores_gemma":[0.002541128,0.0003485027,0.0004073484,0.002433647,0.00009915206,0.0004143085,0.0001331913,0.0002506351,0.00002388887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004047105,"about_ca_system_score_gemma":0.0003570024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001178757,"about_ca_topic_score_gemma":0.00003026651,"domain_scores_codex":[0.9960911,0.0002238113,0.001478498,0.001277757,0.0003859379,0.0005428437],"domain_scores_gemma":[0.9952189,0.001772859,0.0004472114,0.001673231,0.0007015277,0.0001862388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001243848,0.0006140154,0.001858222,0.0003319144,0.001257144,0.000003520229,0.0000571348,0.9868636,0.0001109464,0.0001978576,0.005842493,0.00161937],"study_design_scores_gemma":[0.003776873,0.0003291079,0.00009539257,0.0003772617,0.002344658,0.000002152077,0.0001922369,0.9167008,0.00698821,0.00004031316,0.06885953,0.000293438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00145193,0.002102221,0.9857495,0.005963244,0.001497324,0.002663512,0.00009515094,0.0003830588,0.00009402337],"genre_scores_gemma":[0.6095126,0.003398172,0.357518,0.0209064,0.000602973,0.001792119,0.002997516,0.0001880646,0.003084149],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6282315,"threshold_uncertainty_score":0.9998967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1300011981249453,"score_gpt":0.4542502165788098,"score_spread":0.3242490184538646,"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."}}