THE JERUSALEM POST (January 14, 2019)

Tel Aviv-based health tech company MobileODT’s Automated Visual Evaluation (AVE) machine learning algorithm, validated by the National Cancer Institute and National Library of Medicine, is able to identify problematic lesions far quicker and with far greater reliability than traditional Pap tests.

Cervical cancer is the fourth-most frequent cancer in women, according to the World Health Organization, with an estimated 570,000 new cases in 2018. While often curable if identified at an early stage, approximately 90% of cervical cancer deaths occurred in low- and middle-income countries where prevention programs are limited.

In order to shift the technology from the laboratory into clinical use, a practical application was needed. MobileODT’s EVA colposcope – cleared by the US Food and Drug Administration and currently in use in 29 countries and 50 US healthcare systems – is able to deliver the AVE algorithm at point of care.

“MobileOTD has been working on the algorithm for six years. We’ve developed our EVA system and it’s now in regular use in 29 countries,” MobileOTD CEO Ariel Beery told The Jerusalem Post.

“Through that regular use, we’ve developed the largest data set of cervical images and associated biological data in the world. Using that data set, we were able to create an algorithm that is unparalleled in its diagnostic accuracy, and can deploy it on the same units that were shipped for regular use to our customers around the world.

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