{"id":"W4294711935","doi":"10.3389/fcvm.2022.886549","title":"SlicerHeart: An open-source computing platform for cardiac image analysis and modeling","year":2022,"lang":"en","type":"review","venue":"Frontiers in Cardiovascular Medicine","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Queen's University","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; National Heart, Lung, and Blood Institute; Canarie; National Institutes of Health; Children's Hospital of Philadelphia","keywords":"Workflow; Open source; Computer science; Volume rendering; Python (programming language); Image processing; Visualization; Rendering (computer graphics); Computer vision; Medicine; Artificial intelligence; Computer graphics (images); Software; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001168373,0.001632019,0.001344771,0.0016458,0.0003839883,0.001975372,0.003781856,0.001371862,0.01327298],"category_scores_gemma":[0.002719053,0.0008373996,0.001969971,0.001456601,0.0007003233,0.001780405,0.002289264,0.002394559,0.008996547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004911768,"about_ca_system_score_gemma":0.001907897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002296163,"about_ca_topic_score_gemma":0.002296075,"domain_scores_codex":[0.9992899,0.0001013208,0.00006926209,0.0001043017,0.0003862901,0.00004898255],"domain_scores_gemma":[0.9989797,0.0003666259,0.00008890447,0.0001215876,0.0003087052,0.0001343192],"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":[0.0003011285,0.0000985099,0.00107995,0.005076894,0.0004704953,0.0006429802,0.000324427,0.0254006,0.0174784,0.04503615,0.222271,0.6818196],"study_design_scores_gemma":[0.0001802065,0.0000890703,0.001585398,0.000918598,0.0002013191,0.001448494,0.00005047724,0.06888156,0.01672464,0.03330518,0.8763407,0.000274253],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.002537713,0.03992855,0.8412175,0.001487708,0.001191788,0.0003393179,0.006664148,0.08912086,0.01751243],"genre_scores_gemma":[0.05406756,0.08579876,0.7757086,0.002208678,0.001254072,0.002092662,0.03016026,0.03265299,0.01605641],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01327298,"threshold_uncertainty_score":0.04440254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03512966061220395,"score_gpt":0.2971116432484583,"score_spread":0.2619819826362544,"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."}}