{"id":"W4403271579","doi":"10.1186/s40959-024-00268-4","title":"Building a machine learning-assisted echocardiography prediction tool for children at risk for cancer therapy-related cardiomyopathy","year":2024,"lang":"en","type":"article","venue":"Cardio-Oncology","topic":"Chemotherapy-induced cardiotoxicity and mitigation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Catherine Holmes Wilkins Charitable Foundation; Seattle Children's Research Institute; National Cancer Institute; Rally Foundation","keywords":"Cardiomyopathy; Medicine; Internal medicine; Cardiology; Artificial intelligence; Computer science; Heart failure","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001426922,0.0004266571,0.001169439,0.0004660516,0.0004422094,0.00005718365,0.0001293015,0.0007528219,0.00003522532],"category_scores_gemma":[0.0001849673,0.0003921856,0.002092287,0.0006765995,0.0001510246,0.0001412178,0.00004794988,0.0006955013,0.000008142906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001379414,"about_ca_system_score_gemma":0.0004001821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001184808,"about_ca_topic_score_gemma":0.00001085075,"domain_scores_codex":[0.9972435,0.0003198435,0.0005982708,0.0009075397,0.0003316531,0.0005992334],"domain_scores_gemma":[0.9984223,0.000486421,0.0001965915,0.0004140002,0.0002876248,0.0001930952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001965748,0.000117671,0.06385995,0.0003106951,0.01015508,0.00004068604,0.001185892,0.001805357,0.2808932,0.000170747,0.006563983,0.6329311],"study_design_scores_gemma":[0.01742755,0.004154232,0.06531223,0.0004044366,0.004750846,0.001182641,0.000166638,0.007945468,0.1175091,0.0006712996,0.7795892,0.0008864281],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399388,0.02280077,0.02607698,0.0007929711,0.002553321,0.004840019,0.001309397,0.0008869937,0.0008007681],"genre_scores_gemma":[0.9844563,0.007337553,0.002004917,0.0002882245,0.002118983,0.002316813,0.0008673563,0.000164853,0.0004450023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7730252,"threshold_uncertainty_score":0.999853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506544234302712,"score_gpt":0.2979899067848132,"score_spread":0.2829244644417861,"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."}}