{"id":"W4386269389","doi":"10.48550/arxiv.2308.13568","title":"Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Mitacs","keywords":"Computer science; Noise (video); Artificial intelligence; Process (computing); SIGNAL (programming language); Benchmark (surveying); Fidelity; Noise reduction; Machine learning; Pattern recognition (psychology); Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00108944,0.001050219,0.0008908202,0.0004501203,0.0002563745,0.0009746598,0.001189043,0.001736132,0.002391731],"category_scores_gemma":[0.004433334,0.0004922187,0.001171346,0.0005461349,0.0006026031,0.001238136,0.001026588,0.002153761,0.001248272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000604663,"about_ca_system_score_gemma":0.0007320938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004515006,"about_ca_topic_score_gemma":0.003864749,"domain_scores_codex":[0.9996564,0.0001065342,0.00002386524,0.0001031317,0.0000797466,0.00003028792],"domain_scores_gemma":[0.9987012,0.0008858719,0.00009501213,0.0001094302,0.0001577438,0.00005069402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002372812,0.00008336244,0.0008173936,0.000249247,0.00007658936,0.0002879027,0.0001291038,0.8333853,0.01987829,0.0178906,0.003051018,0.1239138],"study_design_scores_gemma":[0.000004938461,0.00001431188,0.00006464428,0.000005208245,0.000005057772,0.00003544377,0.000003080074,0.9962348,0.0009466887,0.002153498,0.0005259414,0.000006371224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008480214,0.0006839425,0.9889144,0.0002812245,0.0000610745,0.00002772052,0.000153068,0.0005110196,0.0008873625],"genre_scores_gemma":[0.5233755,0.00251177,0.4595796,0.0006538664,0.0002382046,0.0002617891,0.001608166,0.0005195684,0.01125155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004515006,"threshold_uncertainty_score":0.008977413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2042337747753301,"score_gpt":0.2467901952971976,"score_spread":0.04255642052186745,"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."}}