{"id":"W4414686796","doi":"10.2196/79293","title":"AI Applications in Depression Detection and Diagnosis: Bibliometric and Visual Analysis of Trends and Future Directions","year":2025,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Mental Health via Writing","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Depression (economics); Mental health; Focus (optics); Visual methods; MEDLINE","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.000289882,0.0001069954,0.0002821532,0.01939101,0.0002634635,0.00001617144,0.00003214586,0.00009365134,0.00005174687],"category_scores_gemma":[0.000002758234,0.0001062113,0.00002803527,0.03224491,0.00005180957,0.00008224933,0.0000520319,0.000160656,4.755289e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001237076,"about_ca_system_score_gemma":0.00001806308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001954071,"about_ca_topic_score_gemma":0.001914989,"domain_scores_codex":[0.9988068,0.0001463154,0.0003822587,0.0003458813,0.0001033162,0.0002153847],"domain_scores_gemma":[0.9994978,0.0001141864,0.0001346191,0.0001095228,0.00001571634,0.0001281614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003019066,0.0001897473,0.4385121,0.0001029674,0.0000381022,1.544138e-7,0.0006924919,7.89236e-8,0.0000295926,0.00008875061,0.0001089174,0.5602069],"study_design_scores_gemma":[0.0006160568,0.0001284201,0.9884686,0.00004772759,0.00004998854,0.000003636345,0.002526098,0.0002755339,0.00006350764,0.00002069874,0.007735895,0.00006385234],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820837,0.01497824,0.00006952638,0.001574531,0.0001370837,0.0005801153,0.00005604743,0.00003079757,0.0004899748],"genre_scores_gemma":[0.9957544,0.002846338,0.00005749585,0.0004817304,0.00003692495,0.0006892157,0.00004467126,0.000007408341,0.00008182841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5601431,"threshold_uncertainty_score":0.9917234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.017055974860612,"score_gpt":0.4414066292989479,"score_spread":0.4243506544383359,"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."}}