{"id":"W4402900266","doi":"10.3390/diagnostics14192151","title":"Hospital Re-Admission Prediction Using Named Entity Recognition and Explainable Machine Learning","year":2024,"lang":"en","type":"article","venue":"Diagnostics","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Transformer; Machine learning; Gradient boosting; Encoder; Boosting (machine learning); Named-entity recognition; Emergency department; Medicine; Engineering; Random forest","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001702911,0.000845442,0.0005906623,0.002755167,0.0002913036,0.0009045592,0.0009459605,0.0008723085,0.0008034187],"category_scores_gemma":[0.006128887,0.0002046253,0.0009996473,0.001503098,0.0001936667,0.001335155,0.0007862981,0.001073167,0.0004580727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005750752,"about_ca_system_score_gemma":0.0006754401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00574249,"about_ca_topic_score_gemma":0.006738606,"domain_scores_codex":[0.9990067,0.0003551322,0.0001132604,0.0002855469,0.0001523922,0.00008700453],"domain_scores_gemma":[0.9957532,0.002309778,0.0008654887,0.0005099244,0.0004555706,0.0001060515],"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":[0.0005972998,0.0007804071,0.1646367,0.0002922202,0.0007354154,0.00173643,0.0003029767,0.2634589,0.005961417,0.003220166,0.008552165,0.5497258],"study_design_scores_gemma":[0.00001227429,0.0000712205,0.01209518,0.00002174395,0.0000862587,0.0001836838,0.00005304533,0.9794867,0.003889487,0.003141025,0.0009322072,0.00002718476],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4383471,0.003131685,0.5395811,0.001903618,0.0002628448,0.000277745,0.007132537,0.006744455,0.002618882],"genre_scores_gemma":[0.9196163,0.00053125,0.07093401,0.0001242647,0.0001196771,0.00007115534,0.007845288,0.00004794066,0.0007100956],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00574249,"threshold_uncertainty_score":0.0114181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03194079163786902,"score_gpt":0.2788225185716251,"score_spread":0.2468817269337561,"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."}}