{"id":"W3045255701","doi":"10.2196/18715","title":"Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Hemodynamic Monitoring and Therapy","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; National Science Foundation","keywords":"Heart failure; Heart rate variability; Cardiology; Heart rate; Medicine; Internal medicine; Biomedical engineering; Blood pressure","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":[0.003474169,0.001061006,0.00111542,0.0007400407,0.0003054112,0.0007980334,0.0007218166,0.0009003647,0.001933828],"category_scores_gemma":[0.008935581,0.0002531812,0.0007010197,0.0003986138,0.0002894127,0.0005321936,0.0004798831,0.00109025,0.0005572793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003620859,"about_ca_system_score_gemma":0.0006039355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003107843,"about_ca_topic_score_gemma":0.001675043,"domain_scores_codex":[0.9990257,0.0004509108,0.00006979405,0.0002613348,0.0001100786,0.00008216756],"domain_scores_gemma":[0.9946603,0.003881799,0.0002922889,0.0003302284,0.0006504303,0.0001850563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008207938,0.004239285,0.3926646,0.0003257338,0.001491567,0.0008600035,0.0003146796,0.328447,0.007630617,0.0006438298,0.003954346,0.2512203],"study_design_scores_gemma":[0.00006167292,0.001192933,0.01875943,0.00001928934,0.0001091447,0.0001375674,0.00004723696,0.9784899,0.0007460005,0.0001511815,0.0002615946,0.00002412043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9378389,0.0008936533,0.05904264,0.0004071475,0.0001285907,0.0001826675,0.0005015331,0.0003088074,0.0006960767],"genre_scores_gemma":[0.9891249,0.000183831,0.00917327,0.00007437416,0.00004178475,0.0001598354,0.0007167793,0.00002110983,0.0005042251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003474169,"threshold_uncertainty_score":0.01837343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0547465116048545,"score_gpt":0.4110818506331154,"score_spread":0.3563353390282609,"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."}}