{"id":"W4390885406","doi":"10.3390/diagnostics14020181","title":"Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens","year":2024,"lang":"en","type":"review","venue":"Diagnostics","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Iran National Science Foundation; Iran University of Medical Sciences; National Science Foundation","keywords":"Radiomics; Prostate cancer; Glutamate carboxypeptidase II; Somatostatin receptor; Medicine; Neuroendocrine tumors; Radionuclide therapy; Workflow; Artificial intelligence; Computer science; Somatostatin; Cancer; Nuclear medicine; Internal medicine; Database","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":[0.001073569,0.0004569606,0.002242593,0.0003826254,0.00007145321,0.00005435671,0.0001471131,0.0002369293,0.00001302077],"category_scores_gemma":[0.002813235,0.000375413,0.0002359623,0.0005758705,0.000323239,0.00003610343,0.00006953202,0.0007337173,0.000004489766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009050788,"about_ca_system_score_gemma":0.0002771581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006437977,"about_ca_topic_score_gemma":7.655199e-7,"domain_scores_codex":[0.9971865,0.00009967481,0.001495484,0.0006237793,0.0002276311,0.000366868],"domain_scores_gemma":[0.9965535,0.002397231,0.0004201945,0.0003030714,0.0001173729,0.0002086366],"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":[0.00001047014,0.00006745339,0.00003493566,0.2258832,0.0001046329,0.00002700737,0.0002469409,0.000001700488,0.000008767601,0.002031005,0.001937082,0.7696468],"study_design_scores_gemma":[0.0001775594,0.0001100424,0.000001585667,0.1434179,0.00134817,0.0001484696,0.00006540734,0.001382956,0.00002204326,0.0004714503,0.8525186,0.0003358005],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002710669,0.9858546,0.009061739,0.000486166,0.0003043948,0.003998122,0.0001927059,0.00004333488,0.0000317972],"genre_scores_gemma":[0.00001181142,0.9805672,0.01766564,0.000191714,0.0003681723,0.0004791509,0.0005612291,0.0001288685,0.00002620357],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8505815,"threshold_uncertainty_score":0.9998698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703988471765289,"score_gpt":0.3553904720411777,"score_spread":0.3283505873235248,"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."}}