{"id":"W3088009272","doi":"10.2967/jnumed.119.231837","title":"Machine Learning in Nuclear Medicine: Part 2—Neural Networks and Clinical Aspects","year":2020,"lang":"en","type":"review","venue":"Journal of Nuclear Medicine","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of British Columbia; McGill University; Montreal Neurological Institute and Hospital; University of Toronto; Sunnybrook Health Science Centre; University of Waterloo; McMaster University","funders":"Society of Nuclear Medicine and Molecular Imaging","keywords":"Machine learning; Artificial intelligence; Computer science; Artificial neural network; Outcome (game theory); Deep learning; Checklist; Focus (optics); Variable (mathematics); 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":[0.001225269,0.0007569283,0.001266005,0.003001234,0.0002917954,0.001536115,0.0008120207,0.001770201,0.004981719],"category_scores_gemma":[0.002151164,0.0003191388,0.0006347452,0.003265155,0.001179136,0.002780383,0.0008202943,0.002857322,0.001999195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001190069,"about_ca_system_score_gemma":0.001276334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001089394,"about_ca_topic_score_gemma":0.001371017,"domain_scores_codex":[0.9995812,0.0001320174,0.00006337517,0.00005832161,0.0001369207,0.00002821513],"domain_scores_gemma":[0.9983793,0.00115903,0.0001203572,0.00004044903,0.0002470192,0.00005370986],"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":[0.0000476708,0.00008693083,0.0003290546,0.01575253,0.0001112634,0.0001870401,0.0001521567,0.001074696,0.0008674454,0.0213048,0.05578817,0.9042982],"study_design_scores_gemma":[0.000007011333,0.0001096258,0.001401301,0.007818905,0.0000549994,0.00132322,0.00009759067,0.0003988713,0.0004437624,0.01657107,0.9717389,0.00003477705],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001094296,0.9959668,0.0006766688,0.001303999,0.0007991949,0.000006843954,0.00001222462,0.00000760737,0.001117268],"genre_scores_gemma":[0.001131261,0.9941365,0.0006948763,0.001095025,0.001808777,0.00001567945,0.00002958852,0.000006225677,0.001082196],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004981719,"threshold_uncertainty_score":0.01666552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08748182733379006,"score_gpt":0.4194248930144393,"score_spread":0.3319430656806492,"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."}}