{"id":"W4389151000","doi":"10.20944/preprints202311.1644.v1","title":"Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting SSTR and PSMA","year":2023,"lang":"en","type":"review","venue":"Preprints.org","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":2,"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; Workflow; Neuroendocrine tumors; Molecular imaging; Medicine; Computer science; Artificial intelligence; Pathology","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":[0.0007685232,0.000799488,0.0009239009,0.002403275,0.0002913042,0.00162488,0.0006890124,0.0014056,0.002600905],"category_scores_gemma":[0.000955859,0.0003241539,0.0007720002,0.003594485,0.0008880529,0.002239494,0.0006353359,0.00185905,0.001423626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008996688,"about_ca_system_score_gemma":0.0009555321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001217583,"about_ca_topic_score_gemma":0.001020116,"domain_scores_codex":[0.9995875,0.00009395377,0.00005346784,0.00008299334,0.0001437282,0.0000383478],"domain_scores_gemma":[0.9992638,0.0004725516,0.00005851321,0.00002640084,0.0001475068,0.00003128004],"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":[0.00008938597,0.0001468043,0.0005856769,0.0151938,0.000109466,0.0004175518,0.0003346536,0.001965897,0.006218229,0.03954351,0.04229357,0.8931015],"study_design_scores_gemma":[0.00000748987,0.0001604522,0.0009147201,0.002301994,0.00007518421,0.001275789,0.000132285,0.001202223,0.001918781,0.008585705,0.9833779,0.00004753848],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005198541,0.9907395,0.003100778,0.0008252851,0.0005085544,0.00001146956,0.00003074906,0.00003615942,0.004227656],"genre_scores_gemma":[0.004050142,0.9888934,0.003432943,0.0007490369,0.0007490873,0.00002500087,0.00006110508,0.00001673483,0.002022519],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002600905,"threshold_uncertainty_score":0.008700907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1446784791330889,"score_gpt":0.4443657924481916,"score_spread":0.2996873133151027,"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."}}