{"id":"W4391129772","doi":"10.1109/icacta58201.2023.10392702","title":"Deep Learning based Chatbot Architecture for Medical Diagnosis and Treatment Recommendation","year":2023,"lang":"en","type":"article","venue":"","topic":"AI in Service Interactions","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Medical diagnosis; Chatbot; Machine learning; Artificial intelligence; Architecture; Naive Bayes classifier; Classifier (UML); The Internet; Support vector machine; World Wide Web; Medicine","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":[0.0001723501,0.00007630145,0.000077186,0.0001032414,0.0001507677,0.00007385659,0.0001598563,0.00004539127,0.0002557066],"category_scores_gemma":[0.0001420698,0.00006026844,0.0000365652,0.00021663,0.00001087785,0.0001311145,0.00007209913,0.00007316181,0.00004792423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004165195,"about_ca_system_score_gemma":0.00002528532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006559533,"about_ca_topic_score_gemma":0.0004783453,"domain_scores_codex":[0.9993469,0.00004771363,0.0001124899,0.0002287952,0.0001122677,0.0001518275],"domain_scores_gemma":[0.9986256,0.001098286,0.00003206019,0.0001282054,0.00002906027,0.00008683497],"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":[0.000004260943,0.00004543438,0.001599873,0.000008131709,0.00001611856,0.000002707254,0.0006236834,0.001413016,0.00001491547,0.000819025,0.001146328,0.9943065],"study_design_scores_gemma":[0.0003169005,0.0001946154,0.001339954,0.00001233344,0.000004650959,0.000004470939,0.00007425312,0.8952288,0.0004189867,0.0005930704,0.1017375,0.00007449114],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004791825,0.000007763781,0.9312913,0.06272629,0.0002162041,0.0001871146,0.000001104547,0.0003537985,0.0004245648],"genre_scores_gemma":[0.72498,0.0003734197,0.2624324,0.007415149,0.0004409447,0.002304475,0.000209295,0.00004779868,0.001796511],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.994232,"threshold_uncertainty_score":0.2799808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02980216531984404,"score_gpt":0.3134331178912236,"score_spread":0.2836309525713796,"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."}}