{"id":"W4380536977","doi":"10.1109/access.2023.3285596","title":"Artificial Intelligence and Biosensors in Healthcare and Its Clinical Relevance: A Review","year":2023,"lang":"en","type":"review","venue":"IEEE Access","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Innovation and Technology Commission; Research Grants Council, University Grants Committee; Hamad Bin Khalifa University; Qatar National Library; Khalifa University of Science, Technology and Research; Qatar Foundation","keywords":"Computer science; Wearable computer; Health care; Big data; Cloud computing; Data science; Modalities; Artificial intelligence; Relevance (law); Wearable technology; Precision medicine; Data mining; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001671931,0.0004164856,0.002998237,0.000366404,0.00005481757,0.00006749773,0.0003039243,0.000463459,0.00001383278],"category_scores_gemma":[0.004508415,0.0003443586,0.0002449084,0.001281433,0.000130155,0.0001145462,0.0002229884,0.001102234,0.0001177983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001452168,"about_ca_system_score_gemma":0.0006350052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001722182,"about_ca_topic_score_gemma":0.0002222003,"domain_scores_codex":[0.9960085,0.0004531886,0.001852668,0.0009852957,0.0003153081,0.0003850805],"domain_scores_gemma":[0.9957232,0.002845987,0.0004813406,0.000530451,0.0001283463,0.0002906268],"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":[0.000009099903,0.00005036028,0.00008015439,0.2131365,0.00003452983,0.0002090859,0.00001113162,1.246734e-7,3.233172e-8,0.00003033909,0.003200925,0.7832377],"study_design_scores_gemma":[0.00005647145,0.00009438452,0.00007586191,0.3010028,0.0005808923,0.00006618806,0.000002281983,0.00002190052,0.000001838826,0.0001388418,0.6976913,0.0002672735],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001288744,0.9792056,0.000004064579,0.01750749,0.0007195913,0.002294724,0.00003707092,0.00009778201,0.000004774354],"genre_scores_gemma":[0.00004753016,0.9885846,0.0000302368,0.01047378,0.0004992204,0.0001975594,0.00002465305,0.00008609896,0.00005630597],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7829704,"threshold_uncertainty_score":0.9999008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5076975144256946,"score_gpt":0.5825827555928399,"score_spread":0.07488524116714534,"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."}}