{"id":3294,"date":"2024-08-28T06:40:12","date_gmt":"2024-08-28T06:40:12","guid":{"rendered":"https:\/\/www.radisentech.com\/?post_type=publication&#038;p=3294"},"modified":"2024-11-21T07:11:22","modified_gmt":"2024-11-21T07:11:22","slug":"evaluation-of-computer-aided-detection-powered-by-artificial-intelligence-software-in-detecting-tuberculosis-tb-using-radiographs-from-a-tb-mass-screening-program-in-the-philippines","status":"publish","type":"publication","link":"https:\/\/www.radisentech.com\/zh-hant\/publication\/evaluation-of-computer-aided-detection-powered-by-artificial-intelligence-software-in-detecting-tuberculosis-tb-using-radiographs-from-a-tb-mass-screening-program-in-the-philippines\/","title":{"rendered":"Evaluation of computer-aided detection powered by artificial intelligence software in detecting tuberculosis (TB) using radiographs from a TB mass screening program in the Philippines"},"content":{"rendered":"\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-1 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:33.33%\">\n<h2 class=\"wp-block-heading\" id=\"h-published\">Published<\/h2>\n\n\n\n<p>Union Conference on Lung Health (2024)<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-authors\">Authors<\/h2>\n\n\n\n<p>J Lecciones<sup>1<\/sup>, JP Ubalde<sup>1<\/sup>, MR Santiago<sup>2<\/sup>, N Marquez<sup>2<\/sup>, S Guirgis<sup>2<\/sup>, L Stevens<sup>3<\/sup><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-affiliations\">Affiliations<\/h2>\n\n\n\n<p><em><sup>1<\/sup>Tropical Disease Foundation, Philippines,<br> <sup>2<\/sup>Family Health International (FHI) 360, Philippines,<br> <sup>3<\/sup>FHI 360, Asia Pacific Regional Office, Thailand<\/em><\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:66.66%\">\n<p><em>*to be published soon.<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-summary\">Summary<\/h2>\n\n\n\n<p>Chest X-ray equipped with computer-aided detection powered by artificial intelligence software (CAD-AI) is a key strategy for TB case finding in the Philippines. Evaluating CAD-AI performance during active case finding in communities can inform its uptake and expansion in TB mass screening programs.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-background\">Background<\/h2>\n\n\n\n<p>The use of chest X-ray (CXR) equipped with computer-aided detection powered by artificial intelligence software (CAD-AI) in TB screening was introduced in 2019. However, expanding the use of CAD-AI in active case finding (ACF) activities is quite challenging due to perceived uncertainty of its performance and usefulness as a relatively new tool.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-intervention\">Intervention<\/h2>\n\n\n\n<p>ACF using symptoms screening and CXR with CAD-AI was implemented in two highly urbanized cities in Metro Manila targeting urban poor communities. CAD-AI provided a threshold score (0-100%) for each radiograph with a pre-specified threshold of 30% indicating presumptive TB. Radiographs were read by experienced radiologists who made dichotomous decisions on whether findings were suggestive of TB. Individuals with presumptive TB either by symptoms, CAD-AI or human readers were advised to submit sputum specimens for Xpert MTB\/Rif testing. The performance of CAD-AI and radiologists in TB detection were compared with reference to Xpert MTB\/Rif test results, using McNemar\u2019s test with 95% confidence intervals (CIs).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-results\">Results<\/h2>\n\n\n\n<p>Between August and October 2023, 20,042 individuals were screened for TB, of whom 3,267 were tested with Xpert MTB-Rif, and 311 bacteriologically confirmed (BC)-TB cases were identified. The sensitivity of CAD-AI and radiologists in detecting TB was the same at 95% (p=0.85), while specificity of CAD-AI was significantly higher than the radiologists (53%, 95% CI [51%, 55%] for CAD-AI vs. 49%, 95% CI [47%, 51%] for radiologists, p&lt;0.001). When combining TB-positive predictions from CAD-AI and radiologists, the sensitivity significantly increased to 99% (p&lt;0.001), and only 3 of 311 BC-TB were missed. However, in this case, specificity decreased compared to either CAD-AI or radiologists (39%, CI [37%, 41%], p&lt;0.001).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conclusion\">Conclusion<\/h2>\n\n\n\n<p>The results suggest that CAD-AI has the potential to become an important tool in promptly and accurately identifying presumptive TB during mass TB screening programs. Hence, increasing uptake and expanding use of CAD-AI should be considered.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button is-style-fill\"><a class=\"wp-block-button__link wp-element-button\">Link to Publication<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<p><\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false},"categories":[],"class_list":["post-3294","publication","type-publication","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.3 (Yoast SEO v22.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Evaluation of computer-aided detection powered by artificial intelligence software in detecting tuberculosis (TB) using radiographs from a TB mass screening program in the Philippines - Radisen<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.radisentech.com\/zh-hant\/publication\/evaluation-of-computer-aided-detection-powered-by-artificial-intelligence-software-in-detecting-tuberculosis-tb-using-radiographs-from-a-tb-mass-screening-program-in-the-philippines\/\" \/>\n<meta property=\"og:locale\" content=\"zh_TW\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Evaluation of computer-aided detection powered by artificial intelligence software in detecting tuberculosis (TB) using radiographs from a TB mass screening program in the Philippines\" \/>\n<meta property=\"og:description\" content=\"Published Union Conference on Lung Health (2024) Author [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.radisentech.com\/zh-hant\/publication\/evaluation-of-computer-aided-detection-powered-by-artificial-intelligence-software-in-detecting-tuberculosis-tb-using-radiographs-from-a-tb-mass-screening-program-in-the-philippines\/\" \/>\n<meta property=\"og:site_name\" content=\"Radisen\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-21T07:11:22+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.radisentech.com\/wp-content\/uploads\/2024\/06\/Site-image.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"675\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u9810\u4f30\u95b1\u8b80\u6642\u9593\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 \u5206\u9418\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.radisentech.com\/zh-hant\/publication\/evaluation-of-computer-aided-detection-powered-by-artificial-intelligence-software-in-detecting-tuberculosis-tb-using-radiographs-from-a-tb-mass-screening-program-in-the-philippines\/\",\"url\":\"https:\/\/www.radisentech.com\/zh-hant\/publication\/evaluation-of-computer-aided-detection-powered-by-artificial-intelligence-software-in-detecting-tuberculosis-tb-using-radiographs-from-a-tb-mass-screening-program-in-the-philippines\/\",\"name\":\"Evaluation of computer-aided detection powered by artificial intelligence software in detecting tuberculosis (TB) using radiographs from a TB mass screening program in the Philippines - 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