<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zaydman MA</submitter><funding>NIH Office of the Director</funding><funding>Burroughs Wellcome Fund</funding><funding>NIH HHS</funding><pagination>103756</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC8299712</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>117</volume><pubmed_abstract>&lt;h4>Objective&lt;/h4>Clinicians order laboratory tests in an effort to reduce diagnostic or therapeutic uncertainty. Information theory provides the opportunity to quantify the degree to which a test result is expected to reduce diagnostic uncertainty. We sought to apply information theory toward the evaluation and optimization of a diagnostic test threshold and to determine if the results would differ from those of conventional methodologies. We used a heparin/PF4 immunoassay (PF4 ELISA) as a case study.&lt;h4>Materials and methods&lt;/h4>The laboratory database was queried for PF4 ELISA and serotonin release assay (SRA) results during the study period, with the latter serving as the gold standard for the disease heparin-induced thrombocytopenia (HIT). The optimized diagnostic threshold of the PF4</pubmed_abstract><journal>Journal of biomedical informatics</journal><pubmed_title>Using information theory to optimize a diagnostic threshold to match physician-ordering practice.</pubmed_title><pmcid>PMC8299712</pmcid><funding_grant_id>CAMS 1019648</funding_grant_id><funding_grant_id>DP5 OD028125</funding_grant_id><pubmed_authors>Brestoff JR</pubmed_authors><pubmed_authors>Jackups R</pubmed_authors><pubmed_authors>Zaydman MA</pubmed_authors></additional><is_claimable>false</is_claimable><name>Using information theory to optimize a diagnostic threshold to match physician-ordering practice.</name><description>&lt;h4>Objective&lt;/h4>Clinicians order laboratory tests in an effort to reduce diagnostic or therapeutic uncertainty. Information theory provides the opportunity to quantify the degree to which a test result is expected to reduce diagnostic uncertainty. We sought to apply information theory toward the evaluation and optimization of a diagnostic test threshold and to determine if the results would differ from those of conventional methodologies. We used a heparin/PF4 immunoassay (PF4 ELISA) as a case study.&lt;h4>Materials and methods&lt;/h4>The laboratory database was queried for PF4 ELISA and serotonin release assay (SRA) results during the study period, with the latter serving as the gold standard for the disease heparin-induced thrombocytopenia (HIT). The optimized diagnostic threshold of the PF4</description><dates><release>2021-01-01T00:00:00Z</release><publication>2021 May</publication><modification>2025-04-05T10:03:31.528Z</modification><creation>2025-04-05T10:03:31.528Z</creation></dates><accession>S-EPMC8299712</accession><cross_references><pubmed>33766781</pubmed><doi>10.1016/j.jbi.2021.103756</doi></cross_references></HashMap>