{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004302463,0.0007854585,0.00525435,0.0004022754,0.00004467844,0.00005675152,0.0003043626,0.0002649975,0.0003652954],"category_scores_gemma":[0.00004419143,0.0004774312,0.0005739671,0.002019436,0.00003346395,0.0000572014,0.0001264083,0.001290494,0.0001221235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001537693,"about_ca_system_score_gemma":0.001346605,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003451635,"about_ca_topic_score_gemma":0.02269433,"domain_scores_codex":[0.9966095,0.0002545037,0.001016037,0.0009159177,0.0006795639,0.0005244795],"domain_scores_gemma":[0.9984923,0.00008168213,0.0003601532,0.0007073649,0.00006796407,0.0002905396],"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":[0.00002120295,0.00002816414,0.000270499,0.8959072,0.0005793531,0.0000570232,0.0005427045,0.000007058216,8.608969e-9,0.00001817782,0.001262369,0.1013063],"study_design_scores_gemma":[0.0001336605,0.0001020398,0.000005659415,0.5470747,0.006466277,0.0000637886,0.00003401956,0.00002417052,3.088447e-8,4.09729e-7,0.4457985,0.0002967178],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000003998739,0.9875979,0.000005993983,0.0005377433,0.000538755,0.009736039,0.0002290817,0.0001803151,0.001170117],"genre_scores_gemma":[0.00005639672,0.9523314,0.000006629395,0.0005321683,0.0004638599,0.03708673,0.0002004123,0.0002159512,0.009106481],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4445362,"threshold_uncertainty_score":0.9997677,"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."}}