Pre-Congress Workshops

Access to this session depends on the capacity of the room.

Access to this session depends on the capacity of the room.

Access to this session depends on the capacity of the room.

This workshop brings together participants from diverse disciplines to examine the rapidly evolving role of artificial intelligence in healthcare. Through collaborative case discussions and guided activities, attendees will analyze how AI differs from traditional health innovations, explore real world examples of bias and unintended consequences, and consider worst case scenarios to design practical mitigation strategies. Participants will leave with a clearer understanding of responsible AI implementation and approaches that advance fairness, accountability, and equity.

Learning Objectives
Collaborate across disciplines and generations to strengthen epistemic diversity.
Analyze how AI differs from previous health innovations in design, application, and pace of development.
Assess AI’s benefits relative to potential harms and develop mitigation strategies informed by worst case scenario analysis
Groups of 5-6 to facilitate discussion
Registration not needed, walk-ins welcome

Digital pathology is no longer an emerging technology – it is the operational backbone of modern pathology practice. Yet as adoption accelerates worldwide, pathology leaders continue to wrestle with a familiar set of challenges: infrastructure complexity, workforce readiness, financial justification, and now the rapid integration of AI-assisted diagnostics.
This companion meeting, presented by the Digital Pathology Association (DPA), equips attendees with the strategic insights and practical tools needed to design, scale, and sustain digital pathology programs built for the AI era.
Presentations will cover the DPA's resources and initiatives supporting the broader digital pathology community, real-world implementation experience drawn from frameworks applied in complex health systems, and financial stewardship strategies – including hands-on guidance using the DPA ROI Calculator for investment planning and cost modeling.
Attendees will leave with actionable frameworks, peer-tested strategies, and a clearer roadmap for building programs that are not just digitized – but durable, scalable, and AI-ready.

Presenter Presentations:
DPA Highlight – Scott Blakely, Hamamatsu, DPA Board President
Financial Stewardship for Digital Pathology Operations – Dr. Orly Ardon, MSKCC, DPA Board Secretary
Designing Digital Pathology Transformation for the AI Era: Four Challenges, One Systems Problem – Dr. David Clark, Nottingham University Hospital NHS Trust, DPA Member

Access to this session depends on the capacity of the room.

This highly interactive pre-congress workshop is designed as a practical, small-group, bring-your-own-laptop session for participants who want to use state-of-the-art large language models (LLMs) and AI tools to accelerate scientific writing and research communication. Working directly on their own projects, participants will learn how to move from raw data and research materials to structured outputs such as data analyses, tables, figures, presentation slides, posters, abstracts, and manuscript drafts within a focused 2 hour session.

The workshop is intended for active researchers who come prepared with their own project materials, including raw data in spreadsheet format and access to major AI platforms. Participants may bring projects at different stages, including early-stage study plans, partially prepared presentations, or ongoing manuscript drafts. The session will emphasize real-time application, prompt design, workflow integration across multiple AI platforms, and critical human oversight to ensure scientific quality and reliability.

By the end of this workshop, participants will be able to:
Build an efficient multi-tool workflow using leading AI platforms such as ChatGPT, Claude, Gemini/NotebookLM, and Genspark for scientific writing tasks.
Use AI tools to assist with data interpretation, preliminary analysis, and creation of publication-ready tables and figures.
Generate and refine abstracts, manuscript sections, figure legends, titles, and references based on their own project materials.
Convert research content into communication-ready outputs, including PowerPoint slides, scientific posters, and visually improved publication materials.
Apply practical strategies for prompt engineering, quality control, fact-checking, and human review when using AI in academic research.

Registration for this workshop is mandatory, as attendance is restricted to the room's capacity. Please register here: https://docs.google.com/forms/d/e/1FAIpQLSf7MTO3h5azUpLVzZt0iCaNNxojV1FlG8wiThDq1bEqWAg9aw/viewform?usp=dialog

This is a focused follow-up workshop continuing the discussions and projects initiated at the Karman Conference on Computational Nephropathology in Aachen in 2025. The meeting will concentrate on concrete progress updates and coordinated planning for collaborative work in computational nephropathology.
Clinical roadmap to applied computational nephropathology - Status and current challenges
Technical roadmap update - short review of developments in computational methods, infrastructure and standardization
How do we annotate kidney structures and lesions? Update on project progress and first results. Discussion of next steps.
Joint initiatives: Identification of opportunities for shared projects, challenges and grant applications.
This workshop is designed to be interactive and future‑oriented. It will bring together clinicians, pathologists, data scientists, AI researchers, and technical partners committed to advancing computational nephropathology.