{"id":"W4391039240","doi":"10.2196/52322","title":"Machine Learning Approaches to Predict Symptoms in People With Cancer: Systematic Review","year":2024,"lang":"en","type":"review","venue":"JMIR Cancer","topic":"Cancer survivorship and care","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Systematic review; CINAHL; Checklist; Medicine; MEDLINE; Cancer; Artificial intelligence; Machine learning; Psychology; Psychological intervention; Computer science; Psychiatry; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01097165,0.001651671,0.0084071,0.005756209,0.0005725455,0.002406351,0.002001663,0.001969681,0.004499924],"category_scores_gemma":[0.0629858,0.0009318441,0.01067289,0.006825251,0.0008402566,0.002557493,0.001130499,0.001600765,0.0003596806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00363994,"about_ca_system_score_gemma":0.01048406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009177741,"about_ca_topic_score_gemma":0.02732236,"domain_scores_codex":[0.9913927,0.003624102,0.00276451,0.0006032684,0.001399719,0.000215645],"domain_scores_gemma":[0.9590694,0.03268561,0.005107992,0.0005493989,0.002351667,0.0002358893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0002080554,0.00001885976,0.001036574,0.9578133,0.01696165,0.00003965554,0.00009796296,0.0001797418,0.00004976524,0.000155487,0.001217409,0.02222165],"study_design_scores_gemma":[0.0004092471,0.0002471318,0.003882467,0.8748747,0.1106808,0.0001711946,0.0001682525,0.0002794045,0.0001143849,0.0004078744,0.008720577,0.00004395438],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0008924472,0.9974849,0.0002579857,0.0002934977,0.000102531,0.0004453705,0.0003292916,0.00001237304,0.0001816575],"genre_scores_gemma":[0.02373461,0.972093,0.001476617,0.0007505417,0.0001256364,0.001406482,0.0002864632,0.000008374352,0.0001181831],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01097165,"threshold_uncertainty_score":0.05802435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06589265971625585,"score_gpt":0.3419835070891101,"score_spread":0.2760908473728542,"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."}}