{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00606272,0.001088514,0.006306524,0.004501101,0.0004457146,0.001862033,0.001575442,0.001617841,0.004822773],"category_scores_gemma":[0.03070349,0.0005856474,0.006940038,0.005338967,0.0005797938,0.001552899,0.001234795,0.001429268,0.0002994299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002915822,"about_ca_system_score_gemma":0.008211852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01143751,"about_ca_topic_score_gemma":0.02960314,"domain_scores_codex":[0.9961793,0.001516216,0.001143369,0.0002893681,0.0007048722,0.0001667707],"domain_scores_gemma":[0.9806222,0.01600366,0.001967632,0.0001910206,0.001057695,0.0001577205],"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":[0.0002976635,0.00003441672,0.001030514,0.9173926,0.01290894,0.00004651416,0.00008702379,0.0002406163,0.00007403709,0.000241869,0.002003105,0.06564274],"study_design_scores_gemma":[0.000467404,0.0003632406,0.005172942,0.884733,0.08999673,0.0002177511,0.0001690247,0.0004203553,0.0001800753,0.0005943918,0.01763934,0.00004579287],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005872312,0.9985155,0.0001138425,0.0002335965,0.00006027509,0.000120791,0.0002096023,0.000006870518,0.0001522884],"genre_scores_gemma":[0.01436095,0.9836863,0.0006417352,0.0005790698,0.00008339793,0.0003486791,0.0001890785,0.000004401723,0.0001064245],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01143751,"threshold_uncertainty_score":0.03206307,"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."}}