{"id":"W2943876388","doi":"10.1016/j.jbi.2019.103188","title":"Using HL7 FHIR to achieve interoperability in patient health record","year":2019,"lang":"en","type":"article","venue":"Journal of Biomedical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":256,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University Health Network","keywords":"Interoperability; Health records; Electronic health record; Computer science; Health information exchange; Health care; Patient data; Knowledge management; World Wide Web; Internet privacy; Health information","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06922708,0.0007876667,0.000964124,0.005648506,0.00164142,0.008039056,0.002941014,0.003391222,0.005387817],"category_scores_gemma":[0.07982551,0.0008067579,0.001326039,0.002386915,0.001498752,0.01010934,0.00799848,0.002905729,0.004436121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002017026,"about_ca_system_score_gemma":0.003761425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007796979,"about_ca_topic_score_gemma":0.004703881,"domain_scores_codex":[0.9467643,0.0281234,0.008908262,0.003466655,0.01021502,0.002522398],"domain_scores_gemma":[0.912063,0.0403854,0.002465424,0.0285257,0.0156951,0.0008654925],"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":[0.001924211,0.001859431,0.04380642,0.001321044,0.0005626338,0.001963351,0.01684948,0.005500755,0.04675435,0.07338616,0.05105504,0.7550171],"study_design_scores_gemma":[0.0006430701,0.001461811,0.04405897,0.002662313,0.001169921,0.002724881,0.01090238,0.1526588,0.2914042,0.1121534,0.3792401,0.0009201785],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07031901,0.000641514,0.8462368,0.004670612,0.0005841489,0.001930811,0.004615685,0.04047011,0.03053115],"genre_scores_gemma":[0.4590895,0.0004048922,0.5014825,0.005449038,0.0004828262,0.001080425,0.01709541,0.00348784,0.0114276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06922708,"threshold_uncertainty_score":0.3661122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08055145132331874,"score_gpt":0.4609389024689929,"score_spread":0.3803874511456741,"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."}}