{"id":"W4402475035","doi":"10.1109/ccece59415.2024.10667100","title":"Efficient Machine Learning Model Deployment in Clinical Decision Support Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Langara College","funders":"","keywords":"Software deployment; Computer science; Decision support system; Decision model; Artificial intelligence; Clinical decision support system; Machine learning; Software engineering","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":[0.002950023,0.0007547009,0.0009794818,0.0007755657,0.0005039971,0.001829175,0.001306607,0.001085213,0.003142446],"category_scores_gemma":[0.01138637,0.0006233217,0.0005416302,0.0008408637,0.0003361196,0.002113292,0.001697873,0.001392242,0.002172688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008942691,"about_ca_system_score_gemma":0.001701154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005425675,"about_ca_topic_score_gemma":0.0030893,"domain_scores_codex":[0.9981996,0.0008794477,0.000158181,0.0002525214,0.0003412157,0.0001691371],"domain_scores_gemma":[0.9971654,0.001495801,0.0001299626,0.0004102555,0.0006653207,0.0001333502],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007690161,0.0003748428,0.006145694,0.000193527,0.0001169896,0.0004727724,0.000233882,0.5810248,0.005986945,0.007920668,0.009669325,0.3870916],"study_design_scores_gemma":[0.00001815833,0.00004562393,0.0002303109,0.00001081425,0.000006013575,0.00002843774,0.00003193151,0.9941094,0.001356439,0.002849154,0.001308123,0.000005665827],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06593693,0.0008454346,0.9206671,0.001627363,0.0002031134,0.0003219735,0.0004756531,0.006837432,0.003085053],"genre_scores_gemma":[0.7561027,0.0005089721,0.2396235,0.0003232799,0.0001167973,0.0003286754,0.001102607,0.000176252,0.001717346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005425675,"threshold_uncertainty_score":0.0156014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2662688734158786,"score_gpt":0.5582197893743303,"score_spread":0.2919509159584516,"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."}}