{"id":"W4406038522","doi":"10.53759/7669/jmc202505044","title":"An Innovative Artificial Intelligence Based Decision Making System for Public Health Crisis Virtual Reality Rehabilitation","year":2025,"lang":"en","type":"article","venue":"Journal of Machine and Computing","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Artificial intelligence; Computer science; Machine learning; Decision tree; Health care; Context (archaeology); Naive Bayes classifier; Triage; Random forest; Digital health; Big data; Clinical decision support system; Support vector machine; Decision support system; Data science; Data mining; Medicine; Medical emergency","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004436162,0.0001128997,0.0004151189,0.00051356,0.0002385447,0.00008782701,0.00009672958,0.00005341848,0.000001748397],"category_scores_gemma":[0.002328165,0.00009543671,0.00008350853,0.0006735894,0.00003343088,0.0001264767,0.00003643214,0.000251316,1.656126e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003727045,"about_ca_system_score_gemma":0.0006239312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005525866,"about_ca_topic_score_gemma":0.00001833494,"domain_scores_codex":[0.9981565,0.0002262529,0.0009745458,0.0002033478,0.0002585491,0.0001808347],"domain_scores_gemma":[0.9958145,0.002424472,0.0006099677,0.0001605675,0.0008934864,0.0000970133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006960877,0.0003796236,0.006036885,0.0006688718,0.00005590911,0.000007664225,0.001684451,0.004861378,0.0001813464,0.005483155,0.00147973,0.9784649],"study_design_scores_gemma":[0.001208794,0.004408077,0.02679923,0.00514623,0.00008597234,0.00005550844,0.006873237,0.949864,0.0003983277,0.002600119,0.002378086,0.0001823983],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2735448,0.0001372337,0.6850252,0.04082491,0.0002376486,0.0001987488,0.000003851218,0.00002205412,0.000005529605],"genre_scores_gemma":[0.9507731,0.000002837927,0.04091602,0.008102174,0.000190449,0.000001614112,0.00000433322,0.000009036213,3.886688e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9782825,"threshold_uncertainty_score":0.3891796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06537455759597292,"score_gpt":0.421275958274205,"score_spread":0.3559014006782321,"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."}}