star

Preliminary Agenda

Welcome Reception & Keynote

5:30-7 p.m.Reception
7-7:15 p.m.

Introductions

Andrea Chapdelaine; President, Hood College
Len Freedman; Chief Science Officer, Frederick National Laboratory for Cancer Research

7:15-8:15 p.m.Keith R. Yamamoto, Vice Chancellor for Science Policy and Strategy; Vice Dean for Research, School of Medicine, Professor of Cellular & Molecular Pharmacology; University of California San Francisco

 

Morning Session: Frontiers for AI in Cancer Research

Integrating mechanistic modeling with AI; Improving measurement and reproducibility; Standards and references; AI model improvement; AI for hypothesis Generation; Cancer Patient Digital Twin.

8:15-8:30 a.m.Introduction 
8:30-9 a.m.

Recent Developments of AI and Cancer Research/Care
Amber Simpson; University of Toronto

9:05-9:35 a.m.

Explainable AI
Trey Ideker; School of Medicine, University of California, San Diego

9:40-10:10 a.m.

AI and Multiscale Cancer Simulations
Fred Streitz; Lawrence Livermore National Laboratory

10:10-10:30 a.m.Break
10:30-11 a.m.

Recent Developments for AI and Cancer
Rachael Callcut; University of California San Francisco

11:05-11:35 a.m.

Recent Developments for AI and Cancer
Ron Kikinis; Harvard Medical School, Brigham and Woman’s Hospital 

11:40 a.m.-12:10 p.m.Recent Developments for AI and Cancer
Robert Gillies; Moffitt Cancer Center
12:15-1:30 p.m.Lunch

Afternoon Session: Bias in AI for Cancer Research

Disparities in data; disparities in models; understanding limits of applicability; addressing disparities at point of care; uncertainty quantification.

1:30-2 p.m.

Bias in AI models; reaching least care/underrepresented/underserved populations
Llana James; University of Toronto

2:05-2:35 p.m.

Global Perspective on AI, Public Health Data, Privacy, and Health Disparities
Michael Green; Queen’s University

2:40-3:10 p.m.

Racial Factors in Cancer Risk Assessment
Oluwadamilola “Lola” Fayanju; University of Pennsylvania 

3:15-3:45 p.m.

Exploring Bias in Data and Implications for AI
Ulas Bagci; Department of Computer Science, University of Central Florida 

3:45-4 p.m.Break
4-5 p.m.

Combined Panel Discussion – Future of AI in cancer research and care
A.M. and P.M. presenters from Day 1

6-7:30 p.m.Dinner
Keynote Speaker (Entertainment provided following Keynote) Maurizio Vecchione, President/CEO Washington Global Health Alliance

 

Morning Session –Translating AI into Cancer 

(Groundshot) Federated learning; Sharing of results; Medical Imaging; Regulatory Solutions; health information exchanges.

8-8:30 a.m.

Health Services research and ground shot
Fabio Moraes; School of Medicine, Department of Oncology, Queen’s University 

8:35-9:05 a.m.

AI in clinical applications
Corey Arnold; UCLA Samueli School of Engineering 

9:10-9:40 a.m.

Opportunities and Challenges for using AI in Research and Clinical Care
Anant Madabhushi; School of Medicine, Case Western Reserve University 

9:40-10 a.m.

Break

 

10-10:30 a.m.

Uses of AI in Medical Imaging
Stephanie Harmon; National Cancer Institute, Molecular Imaging Branch 

10:35-11:05 a.m.

Translating AI into Cancer Practice
Thomas Fuchs; Mount Sinai 

11:30 a.m.-12:30 p.m.

Panel Discussion – AI Ethics and Privacy in Cancer Center

  • Jonathan Green; Director, Office of Human Subject Research, NIH 
  • Barbara Evans; University of Florida 
  • Kenneth Kaitin; Tufts University School of Medicine
  • Stephanie Russo Carroll; University of Arizona 
  • TBD
12:30-1:30 p.m.Lunch
1:30 p.m.Adjourn

 

 

 

  • Len Freedman (FNLCR)
  • Eric Stahlberg (FNLCR)
  • Monica Slate (FNLCR)
  • Deborah Ricker (Hood College)
  • Laurie Ward (Hood College)
  • Ethan Dmitrovsky (FNLCR)
  • Len Freedman (FNLCR)
  • Eric Stahlberg (FNLCR)
  • Peter Choyke (NCI) Jonas De Almeida (NCI)
  • Amber Simpson (Queens Univ) Marti Head (ORNL)
  • Warren Kibbe (Duke)
  • Daniel Rubin (Stanford)
  • Kristin Swanson (Mayo)