{"id":"W4389304750","doi":"10.1016/j.asoc.2023.111123","title":"A disease diagnosis system for smart healthcare based on fuzzy clustering and battle royale optimization","year":2023,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Department of Science and Technology of Jilin Province","keywords":"Computer science; Cluster analysis; Fuzzy logic; Data mining; Artificial intelligence; Machine learning; Fuzzy clustering; Precision and recall; Identification (biology)","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":[0.0004718083,0.0006530025,0.001210633,0.001621342,0.0007749242,0.0007919506,0.0008667071,0.0009074429,0.003896734],"category_scores_gemma":[0.0005992094,0.0002718229,0.0007927763,0.0008559194,0.0001958885,0.0007641343,0.0007006177,0.0003660289,0.001164229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007262058,"about_ca_system_score_gemma":0.001110429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009047728,"about_ca_topic_score_gemma":0.009581814,"domain_scores_codex":[0.999725,0.00003063007,0.0000264284,0.0000950816,0.00008587147,0.00003682081],"domain_scores_gemma":[0.9998003,0.00004265736,0.00001983619,0.00001889204,0.00009191259,0.00002655267],"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":[0.001103485,0.0005824154,0.01337421,0.0003367667,0.0003222343,0.0004510395,0.0001897147,0.1226758,0.04749497,0.004004692,0.02495,0.7845147],"study_design_scores_gemma":[0.00007292077,0.0001499066,0.005148481,0.00001883615,0.0001055625,0.0002440499,0.00005578258,0.9745771,0.0119188,0.002592068,0.005058498,0.00005794477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05654013,0.0006280832,0.9232695,0.0006044992,0.0001989625,0.0004321006,0.00108882,0.01207547,0.005162407],"genre_scores_gemma":[0.5129409,0.0004335816,0.4756893,0.0004757961,0.0001167788,0.0004116041,0.00188473,0.0002120853,0.00783515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009047728,"threshold_uncertainty_score":0.01799011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09620213078304012,"score_gpt":0.4027147497461537,"score_spread":0.3065126189631136,"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."}}