LMP Artificial Intelligence in Digital Pathology Community of Interest
T-CAIREM is a member of the multidisciplinary team that plans educational seminars and collaborative opportunities for professionals in Pathobiology. This community is currently involved in identifying pilot collaborative projects, developing AI-powered prognostic prediction models leveraging LMP’s whole-slide imaging and T-CAIREM’s computational infrastructure, and designing standardized validation protocols that address regulatory requirements.
Dr. Lingxin Zhang
• Staff Pathologist in the Department of Pathology and Laboratory Medicine, Mount Sinai Hospital,
• Assistant Professor in the Department of Laboratory Medicine and Pathobiology, University of Toronto
What are your goals for this Community?
Our primary goal is to bridge the translational gap between AI development and clinical validation by creating a collaborative, multidisciplinary network of pathologists, scientists, and engineers. We aim to leverage resources like T-CAIREM and the Health Data Nexus to establish best practices for implementing AI in digital pathology across hospital sites.
What inspired your interest in using AI for digital pathology?
The shift was accelerated by the COVID-19 pandemic, which highlighted the necessity of digital workflows and remote work. I am inspired by the capability for AI to increase diagnostic accuracy and streamline repetitive tasks, provided these tools are pathologist-led and tailored to our local disease spectrum and workflows. Looking ahead, AI and digital pathology hold significant potential for educating the next generation of pathologists and mitigating workforce shortages in underserved areas by supporting community practice.
How will this community advance digital pathology and AI?
The community facilitates faculty development workshops and regular online meetings to share the latest policy updates, research, and technical guidelines. We provide a space to discuss critical issues such as data privacy, ethics, and the change management required to support everyone from histology technicians to trainees. We are planning in-person workshops for 2026 that provide a dedicated space for dialogue on AI implementation, allowing attendees to socialize and exchange innovative ideas during interactive sessions.
How do people join?
Interested individuals can sign up through our dedicated COI link. Our community is highly inclusive; we welcome U of T faculty, students (trainees), and learners, as well as collaborators from non-U of T organizations and industry partners who are interested in advancing digital pathology.