{"id":"W4415793482","doi":"10.1161/circ.152.suppl_3.4373117","title":"Abstract 4373117: Quantum Computing based Echocardiographic Diagnosis and Analysis in Congenital Heart Disease: Feasibility and Superiority to conventional Deep Learning Approaches","year":2025,"lang":"en","type":"article","venue":"Circulation","topic":"Congenital Heart Disease Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Deep learning; Convolutional neural network; Quantum computer; Heart disease; Generalization; Medical diagnosis; Artificial neural network; Quantum","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000687923,0.0004268342,0.0002784984,0.0002779287,0.0001386024,0.0004597396,0.0005784012,0.0006025571,0.003539141],"category_scores_gemma":[0.001647214,0.0001290885,0.000219289,0.0003278327,0.0003722354,0.0006154355,0.0004746773,0.0005021648,0.0005742695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005452891,"about_ca_system_score_gemma":0.000943662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00523176,"about_ca_topic_score_gemma":0.005423753,"domain_scores_codex":[0.9997537,0.00004849638,0.00001143174,0.00006353813,0.0001006759,0.00002214874],"domain_scores_gemma":[0.9994893,0.0001729382,0.00004384672,0.00006580854,0.0001827616,0.00004524986],"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":[0.001042988,0.0005411793,0.02090704,0.0003957023,0.0002593703,0.0003970711,0.0001030328,0.204094,0.1007172,0.009681855,0.01789762,0.643963],"study_design_scores_gemma":[0.00004329327,0.0001721134,0.003510786,0.0000162487,0.000027129,0.00009466821,0.0000107179,0.973187,0.01922931,0.001932357,0.001764459,0.00001191611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5990648,0.002937783,0.3806576,0.002187764,0.0003309082,0.0002062758,0.001235189,0.0041007,0.009278881],"genre_scores_gemma":[0.9165153,0.0005382937,0.07769907,0.0001741582,0.00008587803,0.00006576953,0.001138194,0.00009644262,0.003686803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00523176,"threshold_uncertainty_score":0.01183963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04340708411025869,"score_gpt":0.3010949097258684,"score_spread":0.2576878256156098,"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."}}