{"id":"W4392807024","doi":"10.3390/biomedinformatics4010047","title":"Generative Pre-Trained Transformer-Empowered Healthcare Conversations: Current Trends, Challenges, and Future Directions in Large Language Model-Enabled Medical Chatbots","year":2024,"lang":"en","type":"article","venue":"BioMedInformatics","topic":"AI in Service Interactions","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Toronto Metropolitan University; University Health Network","funders":"Canadian Institutes of Health Research; York University","keywords":"Generative grammar; Transformer; Computer science; Health care; Data science; Artificial intelligence; Engineering; Political science; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01117551,0.0009568823,0.001066058,0.001274629,0.000850761,0.004110214,0.003537854,0.002512992,0.009301511],"category_scores_gemma":[0.03012649,0.0005946774,0.0009445443,0.0007994118,0.002506851,0.007133941,0.005149136,0.002356926,0.00387086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001552888,"about_ca_system_score_gemma":0.00251946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001546486,"about_ca_topic_score_gemma":0.001496462,"domain_scores_codex":[0.9911892,0.006405294,0.0003118238,0.0008299766,0.001012665,0.0002511005],"domain_scores_gemma":[0.9704592,0.02606013,0.0005163512,0.001349827,0.001105169,0.0005092811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005988572,0.0004322108,0.003679086,0.009069762,0.0002039552,0.0006864171,0.01520686,0.02298453,0.01497947,0.0993672,0.01712812,0.8156636],"study_design_scores_gemma":[0.0001919027,0.0008517164,0.003076494,0.005304735,0.0002833553,0.002083648,0.009780975,0.2749975,0.02057785,0.230841,0.4515709,0.0004399714],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.03588245,0.04839373,0.8613737,0.01332339,0.001147832,0.0006238989,0.0007729624,0.006811284,0.03167081],"genre_scores_gemma":[0.54362,0.02470756,0.4066798,0.004389653,0.0009623991,0.001616356,0.002360874,0.001120278,0.01454294],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.01117551,"threshold_uncertainty_score":0.05910248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02195279692973618,"score_gpt":0.3209466085783576,"score_spread":0.2989938116486214,"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."}}