{"id":"W7160626563","doi":"10.1109/icscss64956.2025.11501031","title":"Smart Clinical Decisions with AI: Streamlined Segmentation and Classification for Personalized Care","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Personalized medicine; Key (lock); Field (mathematics); Personalization","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":[0.001973598,0.001196275,0.001405966,0.002147829,0.0006227395,0.003000749,0.002202046,0.001882481,0.007105974],"category_scores_gemma":[0.009443048,0.0007095957,0.00107068,0.001701676,0.001068456,0.002717372,0.002103653,0.003139036,0.005041394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001235477,"about_ca_system_score_gemma":0.001835156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005178445,"about_ca_topic_score_gemma":0.005759605,"domain_scores_codex":[0.9985997,0.0004942424,0.0001284425,0.0003660029,0.0003142393,0.00009727255],"domain_scores_gemma":[0.9969487,0.001766767,0.0002606035,0.0004113623,0.0004191398,0.0001934341],"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":[0.0004744983,0.0002978966,0.004398752,0.0005781009,0.000181703,0.0003307523,0.0003942996,0.05733439,0.008989023,0.01170871,0.05210679,0.8632051],"study_design_scores_gemma":[0.0001272522,0.000308121,0.003873636,0.0004530355,0.0002417387,0.0008162205,0.0004638548,0.7239302,0.0135033,0.1697701,0.08631861,0.000193913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007359409,0.006646729,0.9576956,0.01115883,0.0007324564,0.0002591876,0.001229331,0.007783248,0.007135123],"genre_scores_gemma":[0.2353332,0.008058553,0.7401835,0.004843074,0.001729231,0.0004771316,0.002686748,0.001069991,0.005618581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007105974,"threshold_uncertainty_score":0.02377188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07210751975065278,"score_gpt":0.4308034812866149,"score_spread":0.3586959615359622,"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."}}