{"id":"W4408324807","doi":"10.32628/cseit25112419","title":"Predictive Analytics and Machine Learning in Healthcare: A Comprehensive Framework for Clinical Implementation","year":2025,"lang":"en","type":"article","venue":"International Journal of Scientific Research in Computer Science Engineering and Information Technology","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tekna Plasma Systems (Canada)","funders":"","keywords":"Predictive analytics; Health care; Analytics; Computer science; Data science; Artificial intelligence; Machine learning; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007330054,0.00006483945,0.0001758029,0.004334328,0.0003490235,0.0001200781,0.0004520468,0.0001361659,0.000002017673],"category_scores_gemma":[0.001779869,0.00006048896,0.00001959696,0.001780243,0.0005262232,0.001060184,0.0003236284,0.001334835,0.000001511308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003753267,"about_ca_system_score_gemma":0.0008031203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001067531,"about_ca_topic_score_gemma":0.00005826835,"domain_scores_codex":[0.9977666,0.0001265861,0.001085192,0.0001728765,0.0005025113,0.0003462988],"domain_scores_gemma":[0.9957888,0.001366036,0.000252859,0.0001007485,0.002413463,0.00007808944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001231376,0.00003561257,0.4243647,0.0001801181,0.00002094265,0.000005539679,0.002903579,0.008154552,0.00007820783,0.1735307,0.00015482,0.3904481],"study_design_scores_gemma":[0.0006041071,0.0003614999,0.04448641,0.0008428339,0.000001756931,0.00001038305,0.00331737,0.9081478,0.0002132975,0.03334967,0.008588142,0.00007678697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6292033,0.0002441508,0.3495154,0.0176938,0.002824777,0.000479986,0.000008574131,0.00002206611,0.000007882075],"genre_scores_gemma":[0.9780643,0.0004539084,0.02121167,0.0001595222,0.0000753111,0.0000252252,0.000003722239,0.000002434576,0.000003914388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8999932,"threshold_uncertainty_score":0.5799268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1956029873020215,"score_gpt":0.5664706018549168,"score_spread":0.3708676145528954,"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."}}