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Ibex Medical Analytics and UPMC Join Forces for Advancing AI-based Prostate Cancer Diagnostics

July 24, 2018

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TEL AVIV, Israel, July 24, 2018 /PRNewswire/ -- Ibex Medical Analytics, a pioneering developer of AI-powered cancer diagnostics, is announcing today its research collaboration with UPMC and digital pathology expert Dr. Liron Pantanowitz, Professor of Pathology and Biomedical Informatics and Vice Chairman of Pathology Informatics at UPMC Shadyside.

In this collaboration, UPMC and Ibex will apply the Ibex Second Read™ (SR) system on prostate core needle biopsies (PCNBs) from UPMC to further validate the performance characteristics of the AI-driven system in prostate cancer diagnosis.

The Ibex SR system has recently been announced as the first AI-driven diagnostic application in pathology to be applied in a clinical setting. It is deployed in the pathology institute of Maccabi Healthcare Services, one of the largest healthcare providers in Israel and Ibex's strategic partner.

"The advent of digital pathology enables the implementation of AI-driven technologies to ensure more accurate and rapid cancer diagnosis in pathology institutes. We believe that systems such as the one developed by Ibex have an important role in advancing routine anatomic pathology practice. We will be assessing the performance of the Ibex Second Read system to determine its potential for implementation at UPMC," stated Dr. Pantanowitz.

"We are excited to be collaborating with UPMC, a world-renowned center for cancer diagnostics. This collaboration will enable us to further demonstrate our system's validity and is a significant milestone in our journey to make pathology labs more accurate and efficient, leveraging cutting edge big data and machine learning technology," said Joseph Mossel, CEO of Ibex Medical Analytics.



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We are pioneering AI-powered cancer diagnostics in pathology. We are a multidisciplinary team of entrepreneurs, data scientists, software engineers and medical experts, working together to realize our vision: Transforming cancer diagnosis with AI and improving patient care.

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