Thursday, February 12, 2026 at 12:00 AM
This grand round has already taken place.
Online Streaming Available
February 12th, 2026 1.00 AMA PRA Category 1 Credit Hours
Description
The field of pathology is rapidly moving toward a digital and AI-enabled future where all pathologists
access, view, diagnose and manage cases using whole slide images (WSIs) and artificial intelligence (AI)
algorithms. As this transformation progresses, it will continue to be critical for pathologists, laboratory
professionals, and other key decision makers to become fluent in the evolving language of AI and digital
pathology (DP) to make the most informed decisions about which specific digital and AI pathology
solutions best meet the needs of their practice environment.
Achieving this fluency will not require learning to code AI applications but will require the acquisition of
foundational levels of knowledge in the areas of DP infrastructure as well as underlying AI, machine
learning and neural network approaches. The focus should be on understanding the strengths and
weaknesses, training requirements, and level of supervision associated with each approach. The depth
of knowledge should be similar to what pathologists and lab professionals already know about other
testing methodologies in routine use such as immunohistochemistry (IHC), next-generation sequencing
(NGS), and polymerase chain reaction (PCR). The goal should be a level of familiarity and comfort in
critically assessing different AI solution options and matching specific pieces of digital pathology
software, AI algorithms and other tools to current and future needs in their laboratory environment.
This educational presentation will provide an overview of the AI pathology field including a primer on
the main ML methods and examples of clinical and precision medicine algorithms from the current
literature. Also discussed will be the AI/ML methods driving the future of the field, including vision
language models, their potential role in pathologist decision support and a discussion of the challenges
facing the field from the technical, regulatory and medicolegal perspectives.
Dates and Times
Start: 2/12/2026 12:00 AM
End: 2/12/2026 12:00 AM
Objectives
1. Describe current AI/ML methods as they pertain to histopathology, including level of
supervision, training and data requirements, pros & cons.
2. Apply AI/ML methods to specific application use cases in pathology practice and precision
medicine, with specific examples from the latest published literature.
3. Recognize future trends in pathology AI/ML including the development and potential use of
large language models (LLMs) and visual language models.
4. Recognize the emerging ethical and medicolegal issues related to the use of AI in pathology,
oncology and the practice of medicine.
Grand Round Files
Speakers
Location
Basic Sciences Tower Level 9, Rm 140
101 Nicolls Rd
Stony Brook , NY 11794
Accreditation
The School of Medicine, State University of New York at Stony Brook, is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
The School of Medicine, State University of New York at Stony Brook designates this live activity for a maximum of 1.00 AMA PRA Category 1 Credits ™. Physicians should only claim the credit commensurate with the extent of their participation in the activity.
Need help with this Grand Round Session?
Please contact the Grand Round coordinator listed below:
Rachel Larin
Department: Pathology Department
Phone: (631) 444-2169
Email: rachel.larin@stonybrookmedicine.edu