{"id":"W4212810051","doi":"10.2196/32344","title":"Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review","year":2022,"lang":"en","type":"review","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Foundation for Research and Technology-Hellas; European Commission","keywords":"mHealth; Medicine; Disease; Diabetes mellitus; Psychological intervention; Wearable technology; Scopus; Health care; Telemedicine; Global health; Cancer; MEDLINE; Wearable computer; Internal medicine; Computer science; Public health; Pathology","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","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01050134,0.001162575,0.009033928,0.0008043739,0.003869143,0.00002755237,0.0005691035,0.0007086266,0.0001756078],"category_scores_gemma":[0.001250147,0.001023001,0.000906648,0.001449793,0.0001385499,0.0001475589,0.0003542148,0.004277663,0.00003383278],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002286909,"about_ca_system_score_gemma":0.01045412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007777236,"about_ca_topic_score_gemma":0.00027835,"domain_scores_codex":[0.9821244,0.006293911,0.005325315,0.002098322,0.0008491132,0.003308954],"domain_scores_gemma":[0.9874102,0.004185941,0.003088549,0.001587758,0.0001799066,0.003547676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000180987,0.00005320314,0.0001375503,0.6344616,0.00009384032,0.000002466082,0.0001431515,0.00000210698,3.408537e-10,0.0006225706,0.001095483,0.3633699],"study_design_scores_gemma":[0.0007600335,0.0001430308,0.00008786893,0.2954902,0.0041208,0.000005492141,0.0001464434,0.0001519887,1.760392e-10,0.00008942706,0.6985437,0.0004610192],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000008419954,0.9351383,0.00006104537,0.001426091,0.0007201146,0.06178504,0.0004992261,0.0002519783,0.0001097506],"genre_scores_gemma":[0.000007466881,0.7345036,0.0001222609,0.005605764,0.0004572612,0.2578354,0.0009361181,0.0002144253,0.0003177407],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6974482,"threshold_uncertainty_score":0.999222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1221742879554253,"score_gpt":0.4790972063826622,"score_spread":0.3569229184272369,"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."}}