An algorithm developed by Zurich-based company dAIgnose is 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.
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).
“My aim is for women in future to receive a reliable diagnosis within a year,” says Fabian Laumer in a press release issued 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). They were supported by the ETH AI Center and their two co-founders, ETH computer science professor Joachim Buhmann and USZ endometriosis specialist Julian Metzler.
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 be achieved by the end of 2025, although the company will still be waiting on various certifications. ce/mm
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