{"id":"W4400308951","doi":"10.1002/advs.202400595","title":"Revolutionary Point‐of‐Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies","year":2024,"lang":"en","type":"review","venue":"Advanced Science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; York University","funders":"Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Wearable computer; Biomarker; Point of care; Biomarker discovery; Wearable technology; Computer science; Disease; Data science; Medicine; Nanotechnology; Embedded system; Biology; Pathology; Materials science; Proteomics","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":[0.0002547019,0.0003416208,0.0008371668,0.0004616974,0.0002087117,0.00004882554,0.0003074258,0.0001482439,0.000001427494],"category_scores_gemma":[0.00442226,0.0002599934,0.0002844971,0.001312926,0.001171638,0.0005971577,0.0003606802,0.0002785951,0.000009913048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005599711,"about_ca_system_score_gemma":0.000941383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001407395,"about_ca_topic_score_gemma":0.000004510906,"domain_scores_codex":[0.99779,0.00001772723,0.0004806003,0.0009221743,0.0004136869,0.0003758286],"domain_scores_gemma":[0.9979168,0.0008560171,0.0002280468,0.0006511876,0.0002461909,0.0001018213],"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":[0.00004773607,0.00005908207,0.00002975457,0.03614918,0.00003731773,0.00002480802,0.00009709198,0.000007152386,0.00005370162,0.0003169635,0.00027551,0.9629017],"study_design_scores_gemma":[0.0001981508,0.0004349693,0.0001170876,0.06753069,0.001685674,0.00003133408,0.0002582842,0.000100921,0.0004133683,0.003667058,0.9251637,0.0003988038],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001199887,0.990344,0.006032392,0.00059017,0.0006418441,0.001880702,0.0001586772,0.0002193161,0.00001284231],"genre_scores_gemma":[0.002503864,0.993001,0.003704104,0.0001105847,0.00003914456,0.0004891375,0.00001725877,0.00004445517,0.00009047207],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9625029,"threshold_uncertainty_score":0.9999852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04882984214508966,"score_gpt":0.3904673908575631,"score_spread":0.3416375487124734,"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."}}