Tribun Health has announced a new partnership with Ibex Medical Analytics, aimed at enhancing cancer diagnostics through the integration of artificial intelligence (AI) tools. The collaboration will allow healthcare providers to access Ibex’s AI-powered diagnostic solutions via Tribun Health’s CaloPix® Information Management System (IMS), a platform recognized for its digital pathology capabilities.
As part of the agreement, Tribun Health will incorporate Ibex’s AI tools—which are designed to assist in the detection and diagnosis of cancers such as prostate, breast, and gastric—into the CaloPix® IMS. These tools, based on advanced deep learning algorithms, are expected to improve the accuracy and efficiency of cancer diagnoses by integrating seamlessly into the workflows of pathologists.
The integration means that cases within the CaloPix® IMS will be automatically analyzed by Ibex’s AI, with results feeding directly back into the platform. This process aims to support more intelligent case triage and slide review, addressing the growing need for AI-driven solutions in healthcare that can enhance diagnostic precision and streamline patient care.
Jean-François Pomerol, CEO of Tribun Health, emphasized that the partnership reflects the company’s commitment to leveraging innovative technologies to empower healthcare providers. Joseph Mossel, CEO of Ibex, also highlighted the potential for this collaboration to improve patient outcomes by integrating AI tools into existing clinical practices.
This partnership marks a significant development in the adoption of AI in healthcare, particularly in cancer diagnostics. It will enable Tribun Health and Ibex to offer their joint solution in key markets, including Canada, the European Union, and the United States.
Tribun Health’s approach to AI in healthcare is built on three core pillars: the development of proprietary algorithms to enhance workflow efficiency and diagnostic accuracy, strategic collaborations with AI leaders like Ibex, and the creation of a generic API that allows for the integration of third-party and custom-developed algorithms. This strategy ensures that pathology laboratories have access to a comprehensive AI-powered ecosystem tailored to their specific needs.