{"id":"W4206792129","doi":"10.1109/bibm52615.2021.9669569","title":"Health Analytics on Big COVID-19 Data","year":2021,"lang":"en","type":"article","venue":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Autoencoder; Computer science; Machine learning; Artificial intelligence; Identification (biology); Analytics; Predictive analytics; Big data; Test data; Coronavirus disease 2019 (COVID-19); Data mining; Data analysis; Predictive modelling; Deep learning; Data science; Disease; Infectious disease (medical specialty); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001878253,0.0008804024,0.0006117293,0.00207167,0.0004966709,0.002035271,0.0007881904,0.0009340023,0.01083732],"category_scores_gemma":[0.006936654,0.0002682378,0.0006658264,0.002250528,0.0003613767,0.001605006,0.002079567,0.001257023,0.004392286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007485028,"about_ca_system_score_gemma":0.0007227627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005097535,"about_ca_topic_score_gemma":0.005664203,"domain_scores_codex":[0.9987875,0.0002987435,0.000126016,0.0002836034,0.0004151367,0.00008906199],"domain_scores_gemma":[0.9958609,0.001879209,0.0002477883,0.0007785461,0.0009359426,0.0002976773],"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":[0.0008931381,0.0002248152,0.03568192,0.001120482,0.0002741032,0.001305433,0.0002811986,0.03392049,0.007243352,0.007471801,0.4075314,0.5040519],"study_design_scores_gemma":[0.0001940951,0.0004740193,0.04920725,0.0005978745,0.0001709874,0.001103391,0.0007470937,0.5362813,0.01499018,0.03549611,0.360512,0.0002257445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1611286,0.01399152,0.3744345,0.04806057,0.009970713,0.002152551,0.2918547,0.05335003,0.04505687],"genre_scores_gemma":[0.4584562,0.006457957,0.2286142,0.004665751,0.003143141,0.0006387002,0.283613,0.001296614,0.01311443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01083732,"threshold_uncertainty_score":0.03625441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.244183654479877,"score_gpt":0.4297195157071462,"score_spread":0.1855358612272692,"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."}}