{"id":280,"date":"2025-01-04T10:37:16","date_gmt":"2025-01-04T10:37:16","guid":{"rendered":"https:\/\/whmnews.ir\/En\/?p=280"},"modified":"2025-01-04T10:37:16","modified_gmt":"2025-01-04T10:37:16","slug":"ai-based-blood-test-detects-the-earliest-signs-of-breast-cancer","status":"publish","type":"post","link":"https:\/\/whmnews.ir\/En\/index.php\/2025\/01\/04\/ai-based-blood-test-detects-the-earliest-signs-of-breast-cancer\/","title":{"rendered":"AI-Based Blood Test Detects the Earliest Signs of Breast Cancer"},"content":{"rendered":"<p style=\"text-align: justify;\"><strong>AI-Based Blood Test Detects the Earliest Signs of Breast Cancer<\/strong><\/p>\n<p style=\"text-align: justify;\">A new study by researchers at the University of Edinburgh reveals a groundbreaking screening method that combines laser analysis with artificial intelligence, marking the first of its kind to identify patients in the early stages of breast cancer.<\/p>\n<p style=\"text-align: justify;\">The research team states that this fast and non-invasive technique detects subtle changes in blood flow during the initial stages of the disease, known as Stage 1a, which are undetectable with current testing methods.<\/p>\n<p style=\"text-align: justify;\">Using this innovative method, researchers successfully identified early-stage breast cancer by optimizing a laser analysis technique \u2013 known as Raman spectroscopy \u2013 and integrating it with machine learning, a type of artificial intelligence.<\/p>\n<p style=\"text-align: justify;\">The method works by directing a laser beam onto blood plasma samples taken from patients. The properties of light, after interacting with the blood, are analyzed using a device called a spectrometer to uncover small changes in the chemical composition of cells and tissues that signal early signs of the disease.<\/p>\n<p style=\"text-align: justify;\">In a preliminary study involving 12 samples from breast cancer patients and 12 healthy individuals, this method achieved a 98% success rate in detecting breast cancer at Stage 1a. The test also distinguished between each of the four main subgroups of breast cancer with over 90% accuracy, enabling patients to receive more effective and personalized treatment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI-Based Blood Test Detects the Earliest Signs of Breast Cancer A new study by researchers at the University of Edinburgh reveals a groundbreaking screening method that combines laser analysis with artificial intelligence, marking the first of its kind to identify patients in the early stages of breast cancer. The research team states that this fast [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":281,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[39],"class_list":["post-280","post","type-post","status-publish","format-standard","has-post-thumbnail","category-technology-health","tag-ai-based-blood-test-detects-the-earliest-signs-breast-cancer"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.1 (Yoast SEO v24.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI-Based Blood Test Detects the Earliest Signs of Breast Cancer - whmnews<\/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:\/\/whmnews.ir\/En\/index.php\/2025\/01\/04\/ai-based-blood-test-detects-the-earliest-signs-of-breast-cancer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI-Based Blood Test Detects the Earliest Signs of Breast Cancer\" \/>\n<meta property=\"og:description\" content=\"AI-Based Blood Test Detects the Earliest Signs of Breast Cancer A new study by researchers at the University of Edinburgh reveals a groundbreaking screening method that combines laser analysis with artificial intelligence, marking the first of its kind to identify patients in the early stages of breast cancer. 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