| 8:30 – 9:00am |
Travel to MIT-IBM AI Lab from the OMNI Hotel Boston Seaport
More details forthcoming
Transportation will be provided with an add-on fee of $25. |
| 9:00 – 10:00am |
Tour of the
MIT-IBM AI Lab
Tour for registered attendees
The MIT-IBM Watson AI Lab is a community of scientists from MIT and IBM Research dedicated to pushing the frontiers of artificial intelligence and translating breakthroughs into real-world impact. Founded in 2017, the Lab works with industry to translate fundamental science into applications that solve immediate problems in the business world and beyond. The Lab currently manages a research portfolio of more than 80 projects, with an emphasis on data-driven, deep learning approaches to understanding language and the visual world and techniques for making large-scale AI systems more efficient and robust. The Lab is also developing AI systems for healthcare and a variety of decision-making applications. In all of its work, the Lab is committed to building trustworthy and socially responsible AI systems.
Host: Hendrik Strobelt, PhD
Senior Research Scientist at IBM Research
Explainability Lead at MIT-IBM Watson AI Lab
Visiting Researcher at MIT
CME credit does not apply to this activity, 35 maximum capacity. Registration is free but you still need to register.
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| 10:00 – 10:30am |
Travel back to OMNI Hotel Boston Seaport
Transportation by bus will be provided with registration
|
| 10:30 – 10:45am |
Coffee & Tea Break
Education Program Begins at 10:45am
Nouveau Room at the OMNI Host Hotel
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10:45 – 11:15am
11:15 – 11:30am |
FDA Final Rule - Update
Q&A/Panel
•Understand the background and historical context behind the FDA-LDT Final Rule.
•Appreciate the shifting legislative, executive, and judicial landscape that may impact rollout for the FDA-LDT Final rule.
•Understand how the rule impacts the lab (largely from a digital pathology and AI perspective), and likewise to the best of what is known, how labs can navigate the FDA-LDT Final Rule.
S. Joseph Sirintrapun, MD
Clinical Director of Digital Pathology, Mass General Brigham
Associate Professor of Pathology, Harvard Medical School
Panel: TBA
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11:30 – 12:15pm
12:15 – 12:25pm
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Pathobabble:
The Convergence of Pathology and ChatGPT
Q&A
This in-the-headlines presentation explores the fascinating and sometimes frightening intersection of artificial intelligence (AI) and pathology by diving into the integration of large language models (LLMs), like ChatGPT, into modern diagnostic techniques. These advancements have the potential to revolutionize the way we work, communicate, and diagnose. While LLMs offer immense potential, they are adjuncts and not replacements for skilled human pathologists. Combining human expertise with technological advancements will shape the future of pathology and improve patient care.
Learning Objective(s):
1. Understand the fundamentals of large language models, such as ChatGPT, and their relevance to pathology.
2. Explore the practical applications of ChatGPT in pathology, including data extraction, report generation, and knowledge synthesis.
3. Review the ethical considerations and potential biases in AI-driven diagnostic tools and their implications for patient care.
Eric F. Glassy, MD, FCAP
Medical Director
Affiliated Pathologists Medical Group
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| 12:30 – 1:30pm |
Luncheon and
ADASP Business Meeting
Joe Lennerz, MD, PhD
ADASP President
Luncheon provided
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| 1:30 – 2:00pm |
The Impact of Artificial Intelligence on Genitourinary Pathology Fellowship Training: A Comparative Analysis of Prostate Needle Biopsy Case Diagnoses
Learning Objectives:
1. AI integration into GU pathology fellowship training to help pre-screen prostate core needle biopsies can help prioritize cases and accelerate measurements.
2. However, AI did not improve (nor negatively impacted) the diagnostic accuracy of the fellow.
3. Drawbacks may include digital slide navigation difficulties, lack of AI integration with the LIS, and reduced faculty interaction impacting mentorship.
Dimitrios Korentzelos, MD
Assistant Professor of Pathology at the University of Pittsburgh
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2:00 – 2:30pm
2:30 – 2:40pm
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AI in Pathology– Ethical Considerations
Q&A
Learning Objectives:
1. Develop of model for how to determine what is "ethical/moral".
2. Gain an appreciation for what "AI" is and how these tools may breech ethical standards including issues of bias.
3. Propose mechanisms to recognize and mitigate the above problems.
Emma E. Furth, MD
Professor of Pathology and Laboratory Medicine. Hospital of the University of Pennsylvania
Dimitrios Korentzelos, MD
Emma E. Furth, MD
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2:40 – 3:10pm
3:10 – 3:20pm |
Automation in the Surgical Pathology Lab
Q&A
Automation aims to use devices to replace or supplement human efforts in standard processes. The surgical pathology laboratory can benefit from automation, especially as we look towards improving process efficiency while maintaining diagnostic accuracy in an era of workforce challenges. This session will highlight a variety of available options for automation in surgical pathology.
Learning Objectives:
1. Describe how automation can be used in the surgical pathology laboratory.
2. Examine benefits and challenges of use of automation in the surgical pathology laboratory.
3. Apply your understanding of automation in surgical pathology laboratory to use in your workspace.
Jennifer J. Findeis-Hosey, MD
Vice Chair of Educational Programs
Acting Director of Surgical Pathology
Associate Professor
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| 3:20 – 3:30pm |
Closing, final thoughts
Joe Lennerz, MD, PhD
ADASP President
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| 7:30 – 9:00pm |
ADASP Member Cocktail Networking Reception
OMNI Hotel Boston Seaport
Room: Nouveau
After the USCAP opening reception
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