{"id":"W3212899834","doi":"10.2196/32662","title":"Machine Learning–Based Hospital Discharge Prediction for Patients With Cardiovascular Diseases: Development and Usability Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Iran Telecommunication Research Center; Korea Health Industry Development Institute","keywords":"Usability; Computer science; Medicine; Medical emergency; Human–computer interaction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008685411,0.0008431447,0.000625767,0.001347847,0.000298772,0.001103086,0.001169906,0.0007688737,0.001330229],"category_scores_gemma":[0.034376,0.0003210898,0.0009899178,0.001041306,0.0002645502,0.001516302,0.0009045739,0.001002271,0.0005791638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00080036,"about_ca_system_score_gemma":0.000958395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006031896,"about_ca_topic_score_gemma":0.004609854,"domain_scores_codex":[0.9959717,0.002360085,0.0004163784,0.0005570319,0.0005634578,0.000131194],"domain_scores_gemma":[0.972453,0.02162899,0.0006509827,0.001289992,0.003576021,0.0004009561],"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":[0.001994221,0.009524482,0.3542906,0.001709055,0.0008154938,0.0007950789,0.003244768,0.03795809,0.003878697,0.001104122,0.01354601,0.5711394],"study_design_scores_gemma":[0.0006416554,0.004099786,0.1762429,0.0005255528,0.0006067232,0.0006692295,0.002445596,0.7966363,0.005938925,0.001784431,0.01024686,0.0001619707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627714,0.0003777252,0.02938663,0.0004352907,0.0001055543,0.001452247,0.00214698,0.001719752,0.001604362],"genre_scores_gemma":[0.9299989,0.0003233844,0.06278013,0.0001144084,0.00003336632,0.001138802,0.004841088,0.0000747724,0.000695141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008685411,"threshold_uncertainty_score":0.04593337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007607718083775431,"score_gpt":0.2546359990920832,"score_spread":0.2470282810083078,"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."}}