{"id":"W3216498462","doi":"10.2196/27024","title":"A Smartphone-Based Decision Support Tool for Predicting Patients at Risk of Chemotherapy-Induced Nausea and Vomiting: Retrospective Study on App Development Using Decision Tree Induction","year":2021,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Nausea and vomiting management","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Decision tree; Medicine; Clinical decision support system; Medical record; Naive Bayes classifier; Nausea; Machine learning; Logistic regression; Chemotherapy-induced nausea and vomiting; Emergency medicine; Intensive care medicine; Artificial intelligence; Computer science; Decision support system; Internal medicine; Support vector machine; Antiemetic","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":[0.002112485,0.0004063228,0.0004457554,0.001117235,0.0002160728,0.0005623989,0.0003568999,0.0004359232,0.0008722126],"category_scores_gemma":[0.01346062,0.0002209956,0.000531185,0.000606821,0.0001705217,0.0006566975,0.0004570984,0.0004182094,0.000420103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002858987,"about_ca_system_score_gemma":0.000405818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001343189,"about_ca_topic_score_gemma":0.001531212,"domain_scores_codex":[0.9987986,0.0004682305,0.0001706711,0.0001659035,0.0003087126,0.0000878377],"domain_scores_gemma":[0.9908971,0.006240305,0.0008974476,0.000274933,0.001366493,0.0003237872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001242871,0.002136946,0.8602898,0.0003849215,0.0001586521,0.001275427,0.001498305,0.0007533127,0.001147376,0.0001091748,0.001827686,0.1291755],"study_design_scores_gemma":[0.000271148,0.008492709,0.924425,0.0003651923,0.0005505779,0.003549272,0.003762677,0.04928686,0.004257601,0.0003322809,0.004602236,0.0001043703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976554,0.0001911583,0.0009317545,0.00007298075,0.00001115064,0.0002307624,0.0005138975,0.00004028639,0.0003524499],"genre_scores_gemma":[0.9946347,0.0002790442,0.003745226,0.00009704493,0.000009911532,0.0002019111,0.0006712254,0.00001108293,0.0003498135],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002112485,"threshold_uncertainty_score":0.011172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05814428043569085,"score_gpt":0.3727631051376762,"score_spread":0.3146188247019853,"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."}}