{"id":"W4415721970","doi":"10.18280/ts.420507","title":"Advanced Cardiac Monitoring via IoT: A CNN-TCN Hybrid Model for Accurate Clinical Decision Making","year":2025,"lang":"","type":"article","venue":"Traitement du signal","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clinical decision making; Key (lock); Cardiac monitoring; Remote patient monitoring; Decision model","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002952408,0.0007662075,0.001579624,0.000589353,0.0008345918,0.00007050014,0.0005788892,0.0007372566,0.0000720791],"category_scores_gemma":[0.0008046042,0.000794458,0.000831208,0.0005784769,0.0002378732,0.000243487,0.0002941475,0.001494021,0.00004235732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006345957,"about_ca_system_score_gemma":0.0008580313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001131788,"about_ca_topic_score_gemma":0.000002259933,"domain_scores_codex":[0.9931327,0.000286362,0.00287982,0.001437271,0.0007473871,0.001516487],"domain_scores_gemma":[0.9952182,0.002330902,0.0006242842,0.0008798743,0.0005462175,0.0004005235],"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":[0.004656378,0.0006192901,0.07468592,0.0009553154,0.0007170634,0.00005491931,0.000431958,0.008628985,0.001785235,0.0004952627,0.0007400644,0.9062296],"study_design_scores_gemma":[0.01157983,0.002927133,0.01917713,0.01267804,0.00160058,0.000009152562,0.0007201438,0.9293603,0.01037469,0.004232318,0.006168718,0.001171931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5631331,0.003337106,0.4219885,0.000667156,0.007645752,0.002727923,0.00008810009,0.0002577419,0.0001546789],"genre_scores_gemma":[0.9703898,0.0009958803,0.02500831,0.0003972874,0.002216815,0.0005451679,0.00003212117,0.00008751151,0.0003270415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9207314,"threshold_uncertainty_score":0.9994506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07325343225412778,"score_gpt":0.4227225971260273,"score_spread":0.3494691648718995,"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."}}