James D. Thomas, O. Madalina Petrescu, Soundos K. Moualla, Mike Dobbles, J. Clay Hays, Evelio Rodriguez, Glenn R. Barnhart. (2022). Artificial intelligence to assist physicians in identifying patients with severe aortic stenosis. doi.org\/10.1016\/j.ibmed.2022.100059.<\/p>\n
View article<\/a><\/strong><\/p>\n\n\n Severe\u00a0aortic stenosis<\/a>\u00a0(AS) remains a life-threatening form of valvular heart disease. Missed diagnosis of severe AS can lead to a delay in\u00a0treatment<\/a>\u00a0and poor outcomes, but there are limited tools available to help physicians minimize the risk of missed diagnoses. Here, a Diagnostic Precision Algorithm was developed from a de-identified dataset of 1,147,157 echocardiographic reports from 35 institutions to help physicians identify\u00a0patients<\/a>\u00a0who may have incorrectly not received a severe AS diagnosis and prioritize these findings for secondary clinical review. Inclusion criteria required the presence of three standard Doppler indices (aortic valve area [AVA], jet velocity [JV], and mean pressure gradient [MPG]), with at least one in the severe AS range (per AHA\/ACC criteria), and documented assessment of AS severity. Included reports were divided into training\/validation (N\u00a0=\u00a018,040) and test (N\u00a0=\u00a04,533) datasets. Using a decision tree algorithm, a Severe AS Index that estimates the likelihood that a patient with similar values would have severe AS diagnosed was developed from the training\/validation dataset using AVA, JV, and MPG measurements, as well as\u00a0left ventricular ejection fraction<\/a>\u00a0(LVEF) when available. This was compared to the reported interpretation of the\u00a0echocardiogram<\/a>, which was extracted using a validated natural language processing algorithm that demonstrated 100% accuracy across a sample of 600 echocardiographic reports. When the prediction of the Severe AS Index and the report interpretation disagreed, the patient was flagged for secondary review. Across the test dataset, the Diagnostic Precision Algorithm successfully predicted the actual severe AS population proportion with an average error of 2.1% points when LVEF was available and 2.2% points when LVEF was not available. The Diagnostic Precision algorithm was highly accurate at identifying the likelihood of severe AS diagnosis and applying this information to prioritize physician follow-up for patients who may have undiagnosed severe disease.<\/p>","protected":false},"excerpt":{"rendered":" James D. Thomas, O. Madalina Petrescu, Soundos K. Moualla, Mike Dobbles, J. Clay Hays, Evelio Rodriguez, Glenn R. Barnhart. (2022). Artificial intelligence to assist physicians in identifying patients with severe aortic stenosis. doi.org\/10.1016\/j.ibmed.2022.100059. View article Abstract Severe\u00a0aortic stenosis\u00a0(AS) remains a life-threatening form of valvular heart disease. Missed diagnosis of severe AS can lead to a […]<\/p>\n","protected":false},"author":1,"featured_media":6201,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_eb_attr":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[9],"tags":[93,92,90,97,91,96,94,95],"class_list":["post-3563","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications","tag-ai-model","tag-aortic-stenosis","tag-artificial-intelligence","tag-cardiac-disease","tag-cardiovascular","tag-decision-tree","tag-machine-learning","tag-predictive-modeling"],"acf":[],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/bostonsp.com\/wp-content\/uploads\/2017\/03\/Intelligence-Based-Medicine.png","_links":{"self":[{"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/posts\/3563","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/comments?post=3563"}],"version-history":[{"count":6,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/posts\/3563\/revisions"}],"predecessor-version":[{"id":6246,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/posts\/3563\/revisions\/6246"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/media\/6201"}],"wp:attachment":[{"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/media?parent=3563"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/categories?post=3563"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bostonsp.com\/index.php\/wp-json\/wp\/v2\/tags?post=3563"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Abstract<\/h4>\n