Kayhan Batmanghelich<\/a>, Assistant Professor of Electrical & Computer Engineering, Hariri Institute Junior Faculty Fellow and\u00a0AIR<\/a>\u00a0Affiliate at Boston University, was awarded a $3.1 million competitive renewal R01 grant from the National Institutes of Health\u2019s National Heart, Lung, and Blood Institute. With this grant, Batmanghelich will lead transformative research on Chronic Obstructive Pulmonary Disease (COPD) with collaborators from Boston University College of Engineering, University of Pittsburgh School of Medicine and Brigham and Women\u2019s Hospital.<\/span><\/p>\n \u201cLung function tests and CT scans are standard for diagnosing COPD, but they don\u2019t capture how the disease progresses,\u201d says Batmanghelich. \u201cCurrent radiomics lack sensitivity, and most deep learning models are limited, hard to interpret, and sensitive to scan variations.\u201d<\/span><\/p>\n Batmanghelich and his team will address these challenges by building on their\u00a0<\/span>previous work that used self-supervised deep learning to generate radiomic features that are more generalizable than traditional methods<\/span>. Their approach integrates multi-modal data, including CT imaging, genetic and genomic data, <\/span>\u00a0and personalized biomechanical modeling of the tissue<\/span>. This multi-modal framework will enable more accurate disease subtyping and earlier, patient-specific predictions of COPD progression. A key goal is ensuring that the AI-generated insights are clinically interpretable and trusted by physicians.<\/span><\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" AI-driven approach integrates Multi-Modal Data and Biomechanics for Better Diagnosis and Tracking of Chronic Obstructive Pulmonary Disease (COPD)<\/p>\n","protected":false},"author":18241,"featured_media":164593,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[236,257,1429,325,287,977,240,907,1137],"tags":[1121,1359,1360,865,372,948,375,771,1361],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts\/164594"}],"collection":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/users\/18241"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/comments?post=164594"}],"version-history":[{"count":6,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts\/164594\/revisions"}],"predecessor-version":[{"id":164622,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts\/164594\/revisions\/164622"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/media\/164593"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/media?parent=164594"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/categories?post=164594"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/tags?post=164594"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"\/eng\/files\/2024\/03\/ece.faculty.24.batmanghelich.jpg\")
COPD is a progressive and heterogeneous disease affecting over 300 million people worldwide.\u00a0The project, titled\u00a0<\/span>\u201cIntegrating Multi-Modal Data and Biomechanics in COPD: Toward Robust and Interpretable Biomarkers for Disease Subtyping and Progression,\u201d<\/span><\/i>\u00a0aims to overcome critical limitations in current diagnostic tools by developing novel, interpretable biomarkers using advanced artificial intelligence.<\/span><\/p>\nRead the whole story at the Hariri Institute website<\/a>.<\/h3>\n