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Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Polysomnography is the standard tool for assessing obstructive sleep apnea (OSA) severity; however, it does not provide information regarding the anatomical site or extent of upper airway obstruction. Drug-induced sleep endoscopy (DISE) serves as a dynamic method to evaluate airway collapse under sleep-like conditions, thereby helping to bridge this gap. However, its clinical utility is limited by inter-observer variability and subjectivity in interpretation. We developed internally and externally validated deep learning models utilizing convolutional neural networks based on EfficientNet-B2 and Attention Multiple Instance Learning to predict the degree of airway obstruction (DISE-V-obs, DISE-OTE-obs) and the primary cause of obstruction (DISE-OTE-cause) using DISE videos from 1904 patients across five Korean hospitals. The F1 scores for DISE-V-obs, DISE-OTE-obs, and DISE-OTE-cause were 84.7%, 74.7%, and 88.2%, respectively. These objective predictions of obstruction degree and primary cause may enhance clinical decision-making and treatment planning for patients with OSA.<\/jats:p>","DOI":"10.1038\/s41746-026-02673-8","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T13:45:51Z","timestamp":1777383951000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Deep learning-based automatic scoring of drug-induced sleep endoscopy in obstructive sleep apnea"],"prefix":"10.1038","volume":"9","author":[{"given":"Jin Youp","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sue Jean","family":"Mun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young Seo","family":"Baik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young Seop","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young Jae","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jayoung","family":"Oh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gwanghui","family":"Ryu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chung-Man","family":"Sung","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sung Jae","family":"Heo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyung Chae","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyun Jik","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyo Yeol","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyu-Sup","family":"Cho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwang Gi","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chae-Seo","family":"Rhee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,28]]},"reference":[{"key":"2673_CR1","doi-asserted-by":"publisher","first-page":"2","DOI":"10.3949\/ccjm.86.s1.02","volume":"86","author":"JV Rundo","year":"2019","unstructured":"Rundo, J. 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