{"id":4483,"date":"2024-08-23T08:37:07","date_gmt":"2024-08-23T12:37:07","guid":{"rendered":"https:\/\/cccsq.ca\/?p=4483"},"modified":"2026-03-24T15:27:42","modified_gmt":"2026-03-24T19:27:42","slug":"daignose-helps-identify-endometriosis","status":"publish","type":"post","link":"https:\/\/cccsq.ca\/en\/daignose-helps-identify-endometriosis\/","title":{"rendered":"dAIgnose helps identify endometriosis"},"content":{"rendered":"\n\n\t
\"\"<\/figure>\n

Zurich – Two Zurich-based researchers, via their company dAIgnose, have developed an algorithm that reliably identifies endometriosis on ultrasound images of the womb. This is often difficult to achieve with the human eye alone. It is hoped that the procedure will remove the need for laborious and costly laparoscopy procedures.<\/h3>\n

An algorithm developed by Zurich-based company\u00a0dAIgnose<\/a>\u00a0is set to assist doctors in the often difficult process of diagnosing endometriosis in future. It automatically analyzes ultrasound images of the womb and the uterus and is able to reliably identify endometriosis growths.<\/p>\n

Ten per cent of women of childbearing age worldwide suffer from these growths of the endometrium, which result in severe pain before and during menstruation. It currently takes an average of eight to twelve years to be diagnosed with endometriosis, and diagnosis is generally obtained via a laparoscopy under general anesthetic. It is hoped that this will now change thanks to the new method developed by dAIgnose, which was established in 2023 as a spin-off from the Swiss Federal Institute of Technology in Zurich (ETH<\/a>).<\/p>\n

\"\"<\/figure>\n

“My aim is for women in future to receive a reliable diagnosis within a year,” says Fabian Laumer in a\u00a0press release<\/a>\u00a0issued by ETH. Laumer, an expert in artificial intelligence (AI) based at the university, developed the algorithm together with gynecologist and professor Michael Bajka from University Hospital Zurich (USZ<\/a>). They were supported by the\u00a0ETH AI Center<\/a>\u00a0and their two co-founders, ETH computer science professor Joachim Buhmann and USZ endometriosis specialist Julian Metzler.<\/p>\n

The algorithm currently shows the endometriosis in color on 2D ultrasound images. By the end of the year, Laumer is aiming to generate a 3D model on which all growths and adhesions are clearly marked. dAIgnose is now seeking additional investors and is holding initial discussions with medical device manufacturers. Market entry could potentially\u00a0be achieved by the end of 2025, although the company will still be waiting on various certifications. ce\/mm<\/p>\n

https:\/\/swisstrade.com\/news\/detail\/news\/daignose-hilft-beim-erkennen-von-endometriose\/<\/a><\/p>\n\n","protected":false},"excerpt":{"rendered":"

Zurich – Two Zurich-based researchers, via their company dAIgnose, have developed an algorithm that reliably identifies endometriosis on ultrasound images of the womb. This is often difficult to achieve with …<\/p>\n

dAIgnose helps identify endometriosis<\/span> Read More \u00bb<\/a><\/p>\n","protected":false},"author":233,"featured_media":4486,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"pmpro_default_level":"","inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","footnotes":""},"categories":[187,203],"tags":[],"class_list":["post-4483","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-infosuisse","category-innovation","pmpro-has-access"],"acf":[],"yoast_head":"\ndAIgnose helps identify endometriosis - Swiss Canadian Chamber of Commerce (Quebec)<\/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:\/\/cccsq.ca\/en\/daignose-helps-identify-endometriosis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"dAIgnose helps identify endometriosis - Swiss Canadian Chamber of Commerce (Quebec)\" \/>\n<meta property=\"og:description\" content=\"Zurich – Two Zurich-based researchers, via their company dAIgnose, have developed an algorithm that reliably identifies endometriosis on ultrasound images of the womb. 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