{"id":"W4297685013","doi":"10.1109/ichi54592.2022.00127","title":"Towards Trustworthy Artificial Intelligence in Healthcare","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 10th International Conference on Healthcare Informatics (ICHI)","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Trustworthiness; Health care; Computer science; Health informatics; Informatics; Data science; Artificial intelligence; Big data; Knowledge management; Data mining; Internet privacy; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001990348,0.0004812649,0.0005347352,0.00122204,0.0007302947,0.0004864877,0.003861018,0.0001628676,0.0007803154],"category_scores_gemma":[0.0002276092,0.0005381183,0.0001853313,0.001744468,0.0001199708,0.001293932,0.0009714197,0.001829714,0.0004187883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001393172,"about_ca_system_score_gemma":0.00138856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00228398,"about_ca_topic_score_gemma":0.001888462,"domain_scores_codex":[0.9932954,0.0004607392,0.002203468,0.0006892793,0.002275858,0.001075301],"domain_scores_gemma":[0.9968768,0.0002248493,0.0007283345,0.001107323,0.0006570433,0.0004056554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001050825,0.0001972866,0.0003986679,0.00007434767,0.00002101579,0.00006411925,0.005823937,0.007201436,0.00002769883,0.8254818,0.0004512283,0.1601533],"study_design_scores_gemma":[0.0001711894,0.001025679,0.0003500613,0.0001272332,0.000004121869,0.0000866459,0.008539687,0.8127678,0.001596092,0.1687775,0.005778559,0.0007753857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1250553,0.0004150571,0.5077378,0.2793742,0.02992355,0.004704431,0.0009698429,0.00149614,0.05032373],"genre_scores_gemma":[0.9830972,0.0002190738,0.006916704,0.00869415,0.0002280775,0.0004571524,0.0001029213,0.00003334974,0.0002513976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8580419,"threshold_uncertainty_score":0.999707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09984049810389588,"score_gpt":0.3520785432189064,"score_spread":0.2522380451150105,"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."}}