Pathology Informatics

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Pathology Informatics is a unit within the Department of Pathology at the University of Michigan Health System.

The Division of Pathology Informatics at Michigan Medicine advances the department’s tripartite mission of clinical service, research, and education by building, sustaining, and continuously improving the information systems that make modern pathology possible. At its foundation, the division provides uninterrupted stewardship of the laboratory information systems and interfaces that support anatomic pathology, clinical pathology, molecular pathology, MLabs, and precision oncology services, with a constant focus on result integrity, timely reporting, and dependable enterprise-wide operations. In that sense, Pathology Informatics is both an operational backbone and an innovation engine, translating complex pathology workflows into robust digital infrastructure that directly supports patient care.

Beyond service, the division is committed to developing practical, scalable tools that move the needle for pathology as a discipline, not only for our own institution. Our work spans machine learning, image-based analytics, machine vision for histopathology, search and decision-support tools, and federated data architectures, with an emphasis on solutions that can generalize across laboratories, health systems, and practice settings. That same outward-looking approach extends to digital pathology and global partnerships, where Michigan Medicine has publicly highlighted the role of digital pathology, AI, and sustainable collaboration in strengthening pathology and laboratory medicine, including work aimed at low- and middle-income countries.

Education is the third pillar of the division’s mission and a central part of its identity. Michigan offers a dedicated two-year Pathology Informatics and Pathology Data Architecture fellowship, and the division’s faculty contribute to training the next generation of pathologists, informaticians, and data-driven laboratory leaders. The broader goal is not simply to teach people how to use existing systems, but to prepare them to invent better ones: new tools, new workflows, and new computational approaches that expand pathology’s reach, improve quality and efficiency, and help bring advanced diagnostic capability to communities around the world.