{"id":"W4310641612","doi":"10.1109/tbcas.2022.3226290","title":"A Review of Emerging Electromagnetic-Acoustic Sensing Techniques for Healthcare Monitoring","year":2022,"lang":"en","type":"review","venue":"IEEE Transactions on Biomedical Circuits and Systems","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Computer science; Radar; Remote patient monitoring; Health care; Remote sensing; Sonar; Acoustic sensor; Systems engineering; Real-time computing; Artificial intelligence; Engineering; Telecommunications; Acoustics; 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":[0.0006152403,0.0004297708,0.001686423,0.000371411,0.0002076974,0.00003081433,0.0001749967,0.0002290659,0.00002375305],"category_scores_gemma":[0.00002491949,0.0003916148,0.0003553262,0.0005145531,0.00007249109,0.00004404358,0.000001818132,0.0006715426,8.532177e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002702564,"about_ca_system_score_gemma":0.0001669042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004119292,"about_ca_topic_score_gemma":6.200361e-7,"domain_scores_codex":[0.9975886,0.0001270224,0.001057887,0.0003828599,0.0003753823,0.000468283],"domain_scores_gemma":[0.9987396,0.000525708,0.0001922075,0.0002967308,0.00005277517,0.0001929932],"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":[6.074517e-7,0.00001586664,5.738329e-9,0.2663588,0.0001009492,0.000004661583,0.00003398274,0.00001585873,0.0001173623,0.000001848374,0.0001370384,0.733213],"study_design_scores_gemma":[0.0001281418,0.0002152635,1.824477e-8,0.1767332,0.000947604,0.0003591931,0.00009709451,0.00374448,0.00004625296,0.000002834661,0.8172832,0.0004427537],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[6.450303e-7,0.7145622,0.2823338,0.000008996395,0.001408175,0.001179465,0.000254921,0.0002045675,0.00004717838],"genre_scores_gemma":[0.00136751,0.9975609,0.0001794775,0.00002329363,0.0002259642,0.0004709806,0.00003054593,0.0001114574,0.00002990271],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8171461,"threshold_uncertainty_score":0.9998536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0428933806234618,"score_gpt":0.3099684423899764,"score_spread":0.2670750617665146,"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."}}