{"id":"W4392100000","doi":"10.1148/rycan.230029","title":"Quantitative US Delta Radiomics to Predict Radiation Response in Individuals with Head and Neck Squamous Cell Carcinoma","year":2024,"lang":"en","type":"article","venue":"Radiology Imaging Cancer","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Hospital; Health Sciences Centre; Institute for Clinical Evaluative Sciences; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Terry Fox Foundation","keywords":"Radiomics; Medicine; Head and neck squamous-cell carcinoma; Radiation therapy; Basal cell; Head and neck; Nuclear medicine; Lymph node; Head and neck cancer; Internal medicine; Oncology; Radiology; Surgery","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":[0.00161738,0.0004666868,0.0003753005,0.001073373,0.0001455179,0.0005160762,0.0002376269,0.0003914325,0.0005755802],"category_scores_gemma":[0.004372799,0.0001431749,0.000332377,0.0004178215,0.0002447074,0.0003397093,0.0002757572,0.0002991343,0.0001864823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000224288,"about_ca_system_score_gemma":0.0001674024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001533118,"about_ca_topic_score_gemma":0.001835139,"domain_scores_codex":[0.9994339,0.0002235015,0.00004527084,0.0001254977,0.0001258441,0.00004600564],"domain_scores_gemma":[0.998546,0.0005590146,0.0004029846,0.0001124212,0.0002821901,0.0000974193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006606964,0.0000728365,0.9766534,0.00003339657,0.00006269469,0.00003241466,0.00009750236,0.001067149,0.003072685,0.00002563893,0.0001450321,0.01807658],"study_design_scores_gemma":[0.0000174605,0.0006930138,0.9799536,0.00002345223,0.00007830542,0.0002406024,0.0003344767,0.01600468,0.002114183,0.0001517508,0.0003741233,0.00001428869],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980295,0.0003096205,0.00114998,0.00003453725,0.00001125853,0.00001508602,0.0001398101,0.00001815565,0.0002919517],"genre_scores_gemma":[0.9992392,0.00003632184,0.0005375843,0.00001170984,0.000006756873,0.000007975928,0.00007140217,0.000002284453,0.00008684818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00161738,"threshold_uncertainty_score":0.008553684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032922213436041,"score_gpt":0.3131832130083771,"score_spread":0.3028539908740167,"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."}}