{"id":"W3131552811","doi":"10.3389/frai.2021.613637","title":"Case Report: Utilizing AI and NLP to Assist with Healthcare and Rehabilitation During the COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"Frontiers in Artificial Intelligence","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Calgary; Alberta Health; University of Alberta","funders":"Canadian Institutes of Health Research; University of Alberta; Natural Sciences and Engineering Research Council of Canada; Alberta Health Services","keywords":"Pandemic; Isolation (microbiology); Rehabilitation; Health care; Medicine; Healthcare delivery; Coronavirus disease 2019 (COVID-19); Social distance; Intensive care medicine; Medical emergency; Disease; Physical therapy; Pathology; Bioinformatics; Political science; Infectious disease (medical specialty)","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":[0.0007601525,0.002001086,0.001420729,0.002814982,0.006537558,0.002684895,0.002961564,0.01402182,0.004352529],"category_scores_gemma":[0.008712468,0.0008304098,0.001938636,0.002427136,0.002767158,0.004411079,0.004247351,0.01155819,0.00168529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004916402,"about_ca_system_score_gemma":0.003041486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01835135,"about_ca_topic_score_gemma":0.02149989,"domain_scores_codex":[0.9977728,0.0004627075,0.000210364,0.0004035587,0.0003660702,0.0007844078],"domain_scores_gemma":[0.9970594,0.0009406797,0.0004382561,0.0001908414,0.0002752856,0.001095488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"case_report","study_design_gemma":"case_report","study_design_scores_codex":[0.00003503544,0.0001684795,0.004913982,0.00007225751,0.00001518144,0.9818985,0.002183314,0.0004323733,0.0002409866,0.001880545,0.003822014,0.00433743],"study_design_scores_gemma":[0.00001537349,0.0001022625,0.003030939,0.000229864,0.00002000763,0.9841664,0.002470352,0.001858299,0.0003188543,0.002300095,0.005448622,0.00003887687],"study_design_candidate":"case_report","study_design_consensus":"case_report","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6748766,0.01404835,0.02885599,0.132689,0.004768089,0.001481608,0.002217508,0.0008387204,0.140224],"genre_scores_gemma":[0.9505003,0.00471703,0.01124601,0.01979945,0.002639843,0.0002874384,0.0004694248,0.0001865993,0.0101539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01835135,"threshold_uncertainty_score":0.03648907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1508181958268479,"score_gpt":0.4276888802865019,"score_spread":0.276870684459654,"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."}}