{"id":"W4411141158","doi":"10.1200/edbk-25-472464","title":"Artificial Intelligence for Head and Neck Squamous Cell Carcinoma: From Diagnosis to Treatment","year":2025,"lang":"en","type":"review","venue":"American Society of Clinical Oncology Educational Book","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"","keywords":"Head and neck squamous-cell carcinoma; Medicine; Radiation therapy; Clinical trial; Malignancy; Radiation treatment planning; Oncology; Head and neck cancer; Internal medicine","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":[0.0005199322,0.0003114366,0.003025355,0.00006686028,0.00008837468,0.000009849849,0.0001817277,0.0002994804,0.0001580518],"category_scores_gemma":[0.002170371,0.0002501541,0.001300744,0.0002021404,0.0008610029,0.00001975894,0.00007798682,0.0005398443,0.00001491584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003709123,"about_ca_system_score_gemma":0.005534389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005351683,"about_ca_topic_score_gemma":0.000009318604,"domain_scores_codex":[0.9970575,0.0002051012,0.001625449,0.0006726568,0.000176266,0.0002630035],"domain_scores_gemma":[0.9778502,0.02050094,0.0007868753,0.0003037311,0.0001562132,0.000402065],"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":[0.00006066706,0.001400035,0.002063796,0.001497941,0.0001769012,0.000001296369,0.0002261088,0.000001442041,1.675826e-7,0.0001625244,0.01512926,0.9792799],"study_design_scores_gemma":[0.000317068,0.00287411,0.001389817,0.0009804198,0.001793044,0.000003890011,0.0001449753,0.00008700921,0.000001847385,0.0003429997,0.9918825,0.0001823167],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001768676,0.9538028,0.001086717,0.03967172,0.000703396,0.0017832,0.0001515171,0.00001799951,0.001014023],"genre_scores_gemma":[0.0005423791,0.927671,0.05649464,0.009326101,0.001472378,0.0008634037,0.0003213366,0.000031911,0.003276916],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9790975,"threshold_uncertainty_score":0.9999951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1148008050580933,"score_gpt":0.5053163263542124,"score_spread":0.3905155212961192,"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."}}