{"id":"W3216958961","doi":"10.1016/j.cpet.2021.09.009","title":"Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities","year":2021,"lang":"en","type":"review","venue":"PET Clinics","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"NIH Clinical Center; National Institutes of Health","keywords":"Medicine; Conceptualization; Software deployment; Harm; Population; Disease; Health care; Artificial intelligence; Intensive care medicine; Medical emergency; Pathology; Computer science; Environmental health; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002621642,0.0006231596,0.001745298,0.002468576,0.0004034269,0.002686206,0.0009898014,0.002590834,0.003503037],"category_scores_gemma":[0.00394498,0.0002878486,0.0006638397,0.00342014,0.001497528,0.002988906,0.001181006,0.003720349,0.0009360589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001458743,"about_ca_system_score_gemma":0.00344652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002658967,"about_ca_topic_score_gemma":0.005990824,"domain_scores_codex":[0.9993148,0.0002313281,0.00008045155,0.00007285785,0.0002446152,0.00005606299],"domain_scores_gemma":[0.9943193,0.004216611,0.0003477774,0.00007497423,0.000829066,0.0002123021],"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":[0.00006075368,0.00007053501,0.0004091629,0.01837425,0.0001267011,0.0001183075,0.0001246708,0.0004040932,0.0002835481,0.01423622,0.03695194,0.9288399],"study_design_scores_gemma":[0.00002850778,0.0001144468,0.001915659,0.0243996,0.0002102879,0.0008587678,0.0003428007,0.0003627442,0.0001755189,0.01368284,0.9578577,0.00005124676],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004952729,0.9977663,0.00006814343,0.001523262,0.0001477956,0.000001597765,0.00000732724,0.000002724549,0.0004333887],"genre_scores_gemma":[0.0005343641,0.9983082,0.0001351452,0.0005835966,0.0003075234,0.000002977422,0.000008414852,8.93018e-7,0.00011891],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003503037,"threshold_uncertainty_score":0.0138647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6373791860165721,"score_gpt":0.5657536383199465,"score_spread":0.07162554769662555,"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."}}