{"id":"W4210550903","doi":"10.24908/pocus.v7ikidney.15345","title":"Machine Learning in Point of Care Ultrasound","year":2022,"lang":"en","type":"review","venue":"POCUS Journal","topic":"Ultrasound in Clinical Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; University of Pennsylvania; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Howard Hughes Medical Institute","keywords":"Point of care ultrasound; Computer science; Medical physics; Patient care; Point (geometry); Medical imaging; Point of care; Point-of-care testing; Software; Artificial intelligence; Machine learning; Medicine; Ultrasound; Radiology; Pathology; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008247894,0.0002576263,0.001727707,0.0003351532,0.0001250285,0.00002108033,0.0002895648,0.0001897909,0.005273726],"category_scores_gemma":[0.002194771,0.0001983231,0.0007544251,0.0005204899,0.00007216752,0.00003870212,0.0000729001,0.003804946,0.00004628576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000453749,"about_ca_system_score_gemma":0.0006498395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002929551,"about_ca_topic_score_gemma":0.00001054775,"domain_scores_codex":[0.997341,0.0002974023,0.00139397,0.0002596111,0.0004474364,0.0002606296],"domain_scores_gemma":[0.996362,0.002186903,0.0008537115,0.0003231779,0.00008797201,0.0001862915],"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":[0.00002274209,0.0002314483,0.002012888,0.006728297,0.0001919485,0.0000720431,0.0003384675,0.00000624594,0.000002687609,0.0001284978,0.00021506,0.9900497],"study_design_scores_gemma":[0.0004587727,0.0003042417,0.0001210032,0.004092274,0.0007205723,0.003588187,0.00018031,9.056638e-7,5.366877e-7,0.0002178533,0.9901583,0.0001570126],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003875495,0.9924566,0.00003267476,0.00008032729,0.0001802005,0.0004464504,0.00005494898,0.00002104618,0.006689037],"genre_scores_gemma":[0.0002277575,0.9976191,0.0009648864,0.00004606276,0.0002929175,0.00005370717,0.0002161701,0.00006338731,0.0005160476],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9899433,"threshold_uncertainty_score":0.9984933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07692418482058493,"score_gpt":0.405272962719853,"score_spread":0.328348777899268,"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."}}