Ibex Decision Support
Empower pathologists to make quicker and more accurate diagnosis with state-of-the-art decision-support tools
From the press
Ibex Medical Analytics, a pioneering developer of AI-driven computational pathology cancer diagnosis system, completed an $11 million Series A funding round led by aMoon Fund.
From the press
Maccabi Healthcare Services, which runs a pathology institute responsible for 160,000 histology accessions every year, recently started leveraging Ibex Medical Analytics’ Second Read system.
Ibex has been playing an important role in advancing AI-based technologies in pathology and is the first company to implement an AI-driven diagnostic system in routine clinical use. I am a huge advocate of the work of this company.
Sylvia L. Asa, MD, MPH
Former USCAP President and Chief Pathologist at UHN Toronto
I am deeply impressed with the Ibex Second Read system and with the performance of its algorithms, as well as with how quickly the Ibex team was able to deploy a system and integrate it into the routine clinical workflow of a large pathology institute. This disruptive technology is a game-changer.
Daniel Val Garijo, MD
Pathologist, Laboratoire National de Santé, Luxembourg
I’m extremely happy to be collaborating with Ibex on transforming cancer diagnostics – and thrilled to have deployed the Ibex Second Read system at Maccabi, rendering the Maccabi pathology institute the first in the world to deploy such a system in our routine workflow, and the first to demonstrate the value of AI in reversing a missed cancer diagnosis in real time.
Prof. Varda Shalev, MD, MPH
Managing Director, Morris Kahn & Maccabi Research and Innovation Institue at Maccabi Health care Services
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.