2024 NIH ODSS AI Supplement Program PI Meeting

March 27-28, 2024
11am — 5pm EDT

This meeting is designed to foster the development of a cohesive National Institutes of Health (NIH) AI community by uniting PIs (Principal Investigators) from the FY22 and FY23 Office of Data Science Strategy (ODSS) AI supplement programs for a two-day, virtual gathering that will provide a platform for participants to exchange insights on their projects, celebrate accomplishments, discuss best practices, share lessons learned, and engage in collaborative discussions.

Attendees

Principal Investigators from the following cloud supplement programs have been invited:

Featured Speakers

Susan Gregurick, Ph.D. — Associate Director for Data Science, NIH; Director, ODSS

Dr. Susan K. Gregurick was appointed Associate Director for ODSS at the NIH on September 16, 2019. Under Dr. Gregurick’s leadership, the ODSS leads the implementation of the NIH Strategic Plan for Data Science through scientific, technical, and operational collaboration with the institutes, centers, and offices that comprise NIH. Dr. Gregurick received the 2020 Leadership in Biological Sciences Award from the Washington Academy of Sciences for her work in this role. She was instrumental in the creation of the ODSS in 2018 and served as a senior advisor to the office until being named to her current position.

Laura Biven, Ph.D. — Lead, Integrated Infrastructure and Emerging Technologies, NIH ODSS

Since joining NIH in 2020, Dr. Laura Biven has led the Integrated Infrastructure and Emerging Technologies (IIET) branch in ODSS. She is responsible for strategic planning, coordination, and oversight of programs that integrate independently managed, cloud data resources across the NIH to advance NIH’s vision for an integrated, FAIR biomedical data ecosystem. She also oversees multidisciplinary NIH-wide programs that focus on integrating computational, mathematical, and biomedical research communities around emerging technologies such as artificial intelligence and machine learning, (AI/ML) quantum computing, and digital twins.

Christine Cutillo — Health Data Scientist for AI Ethics, NIH ODSS

Christine Cutillo is a Health Data Scientist for AI Ethics in the ODSS, within the Integrated Infrastructure and Emerging Technologies (IIET) unit. She is responsible for multidisciplinary NIH-wide AI Ethics efforts – focusing on integrating ethics through the AI lifecycle in biomedical research applications. She is highly interested in data-driven scientific and health care innovations that are transparent, ethical, and designed for and with the patient/end user. Prior to joining ODSS, Christine was the Data Science Lead in the Office of the Director at the National Center for Advancing Translational Sciences (NCATS) for three years.

Agenda*

We are looking forward to your participation at the meeting. We encourage you to review our agenda, which will be updated as new information is confirmed, speakers are assigned to breakout sessions, and presentations are uploaded following the event. *Agenda is subject to change.

Day 1

11am-12:25pm ET
WELCOME
Dr. Laura Biven, Lead, Integrated Infrastructure and Emerging Technologies, NIH ODSS

NIH OFFICE OF DATA SCIENCE STRATEGY OVERVIEW
Dr. Susan Gregurick, Associate Director for Data Science, NIH; Director, ODSS
Download Slides ODSS AI ACTIVITIES OVERVIEW & FUTURE VISION
Ms. Christine Cutillo, Health Data Scientist for AI Ethics, NIH ODSS
Download Slides BEGINNING OF THE MEETING POLL
The poll will explore various, relevant topics at the forefront of NIH AI
Ms. Christine Cutillo, Health Data Scientist for AI Ethics, NIH ODSS
12:25-1:25pm ET
BREAKOUT SESSION 1

During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects.


TRACK A

Dr. Alex Federman (Moderator), Professor of Medicine, Icahn School of Medicine at Mount Sinai, Dr. Jalayne Arias, Associate Professor, Georgia State University
A Qualitative Examination of Patients’ and Clinicians’ Perspectives on AI-driven Automated Screening for Cognitive Impairment
Download Slides Dr. Andrew Schaefer, Professor, Rice University
Implementation of a Public Data Challenge for MRI-Guided Tumor Segmentation in Head and Neck Cancer Patients
Download Slides Dr. Lu Tang, Professor, Texas A&M University; Dr. Jinsil Hwaryoung Seo, Associate Professor, Texas A&M University; Dr. Sophia Fantus, Assistant Professor, University of Texas at Arlington
Improving AI Alzheimer Researchers’ Knowledge, Attitudes and Practices of AI Ethics
Download Slides Dr. James V. Lacey Jr., Professor, City of Hope
Strategies for Improving the Readiness of Large-scale Cohort Data for AI/ML
Download Slides TRACK B

Dr. Kyung Sung (Moderator), Associate Professor, University of California, Los Angeles
Detection and Localization of Prostate Cancer: A Structured Multi-Scale Multiparametric MRI Database for AI/ML Research
Download Slides Mr. Trenton Chang, Ph.D. Candidate, University of Michigan
Measuring and Mitigating the Impact of Biases in Laboratory Testing on Machine Learning Models
Download Slides Dr. Levi Waldron, Professor, City University of New York; Dr. Sehyun Oh, Assistant Professor, City University of New York
Improving FAIRness and AI/ML readiness of Bioconductor data resources
Download Slides Dr. Maya Sabatello, Associate Professor of Medical Sciences, Columbia University
Blind/Disability and Intersectional Biases in E-Health Records (EHRs) of Diabetes Patients

Dr. Cathy Wu, Professor and Director, Data Science Institute, University of Delaware
UniProt Knowledgebase to Enable AI/ML Readiness and Applications
Download Slides
1:25-1:35pm ET
BREAK
1:35-2:35pm ET
BREAKOUT SESSION 2
During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects.

TRACK A

Dr. Bankole Olatosi (Moderator), Associate Professor, University of South Carolina
Framing the Ethical-Framework Guided Metric Tool – Lessons Learned
Download Slides Dr. Shivakeshvan Ratnadurai Giridharan, Instructor, Burke Neurological Institute
Development of Deep Learning-based Kinematic Data Acquisition
Download Slides Dr. Amber Simpson, Associate Professor/Canada Research Chair, Queen's University; Ms. Rohan Faiyaz Khan, PhD Student, Queen's University
Ethical Development of Colorectal Cancer Imaging Biomarkers
Download Slides Dr. Rebecca McNeil, Senior Research Statistician, RTI International
Enabling AI/ML Readiness and Modernization of Longitudinal Pregnancy and Cardiovascular Health Data: Lessons Learned
Download Slides TRACK B

Dr. Jennifer Wagner (Moderator), Assistant Professor of Law, Policy, and Engineering and Anthropology, Penn State University
A Synopsis of the PREMIERE Ethics Supplement
Download Slides Dr. Alex Wagner, Principal Investigator, Nationwide Children’s Hospital
Application of Genomic Knowledge Standards to the Genome Aggregation Database
Download Slides Dr. Jessica Sperling, Director, Office of Evaluation and Applied Research Partnership, Duke University; Dr. Whitney Welsh, Research Scientist, Duke University
Machine Learning and The Ethics of Use: Patient and Provider Perspectives on Utilizing Prediction Models in Medical Care
Download Slides Dr. Benjamin Vincent, Associate Professor of Medicine, University of North Carolina at Chapel Hill
ASTOR: Alliance Standardized Translational ‘Omics Resourcse
Download Slides
2:35-2:45pm ET
BREAK
2:45-3:45pm ET
BREAKOUT SESSION 3
During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects.

TRACK A

Dr. Abhinav Jha (Moderator), Assistant Professor, Washington University
Uncertainty Quantification of AI-Based Imaging Algorithms: The Need and Methods
Download Slides Dr. Sriram Neelamegham, Professor/PI, University at Buffalo, State University of New York; Dr. Rudiyanto Gunawan, Associate Professor, State University of New York - Buffalo
Systems Biology of Glycosylation: Extending Mechanistic Analysis Toward AI
Download Slides Dr. Josiah Couch, Postdoctoral Research Fellow, Beth Israel Deaconess Medical Center
Beyond Class Balance: Dataset Diversity and Model Performance in Deep-Learning Classification Tasks
Download Slides Dr. Alexey Terskikh, Associate Professor, Sanford Burnham Prebys Medical Discovery Institute
ImAge Quantitates Ageing and Rejuvenation

TRACK B

Dr. Qing Zeng-Treitler (Moderator), Director, Biomedical Informatics Center, George Washington University
Shedding Light on the Black Box: Using Explainable AI to Enhance Clinical Research
Download Slides Dr. Ranjan Ramachandra, Research & Development Engineer, University of California San Diego
Development of Software for the Optimization and Normalization of 3D Electron Microscopic Data Acquisition to Facilitate Use and Reuse of AI/ML-Based Image Analysis Tools
Download Slides Dr. Joan Casey, Assistant Professor of Environmental and Occupational Health Sciences, University of Washington School of Public Health; Dr. Danielle Braun, Principal Research Scientist, Harvard T.H. Chan School of Public Health
Approaches for AI/ML Readiness for Wildfire Exposures
Download Slides Dr. Amit Majumdar, Division Director, Associate Professor, University of California San Diego
Implementation of Provenance Metadata on Neuroscience Gateway – A Platform for Neuroscience Software Dissemination
Download Slides Dr. Samantha Krening, Assistant Professor, The Ohio State University
An Automated AI/ML Platform for Multi-Researcher Collaborations for a NIH BACPAC Funded Spine Phenome Project
3:45-3:55pm ET
BREAK
3:55-4:55pm ET
BREAKOUT SESSION 4
During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects. Participants from the FY23 NOT-OD-23-082 program will give 10-minute lightning presentations on their project motivation, plan, and expected outcome

TRACK A

Dr. Danton Char (Moderator), Associate Professor, Stanford Medicine
Development of a Method for Identifying Ethical Considerations Arising from Healthcare AI Deployments
Download Slides Dr. Jaehee Kim, Assistant Professor, Cornell University
Towards AI/ML-Enabled Molecular Epidemiology of Mycobacterium Tuberculosis

Dr. Jodyn Platt, Associate Professor, University of Michigan
Attitudes of Cancer Patients About the Use of AI in Clinical Care: A Nationwide Survey
Download Slides Dr. Katherine Yates, Rheumatology Fellow, University of North Carolina at Chapel Hill
Development of an AI/ML-Ready Knee Ultrasound Dataset in a Population-Based Cohort 
Download Slides Dr. Yann Le Guen, Senior Biostatistician, Stanford University
PREcision Care In Cardiac ArrEst - ICECAP (PRECICECAP)
Download Slides TRACK B

Dr. Clifton Fuller (Moderator), Professor, UT MD Anderson Cancer Center
Leveraging MRI applications for FAIR and Open (Re)Use
Download Slides Dr. Alaa Youssef, Post-Doctoral Scholar, Stanford University School of Medicine
Ethical Considerations in the Design and Conduct Clinical Trials of AI: A Qualitative Study of Investigators' Experiences with Autonomous AI for Diabetic Retinopathy
Download Slides Dr. Bofan Song, Associate Research Professor, University of Arizona
Improving AI/ML-Readiness of Data Generated from NIH-Funded Research on Oral Cancer Screening
Download Slides Dr. Bobbie-Jo Webb-Robertson, Division Director, Biological Sciences, Pacific Northwest National Laboratory
Generating AI/ML-Ready Data for Type 1 Diabetes
Download Slides Dr. Diana Vera Cruz, Bioinformatician, University of Chicago; Dr. Romuald Girard, Assistant Professor, University of Chicago
Optimizing Diagnostic and Prognostic Biomarkers of CASH using Machine Learning
Download Slides
4:55-5pm ET
CLOSE
Ms. Christine Cutillo, Health Data Scientist for AI Ethics, NIH ODSS

Day 2

11am-11:10am ET
INTRODUCTION
Ms. Christine Cutillo, Health Data Scientist for AI Ethics, NIH ODSS
11:10am-12:10pm ET
BREAKOUT SESSION 5
This interactive breakout session, led by NIH program officers, gives participants time to discuss AI barriers, challenges, and opportunities (including novel ideas and future directions). Participants will be divided into a few virtual rooms; a report-back session is scheduled for later in the day.

TRACK A

Ms. Christine Cutillo (Moderator), NIH ODSS
Dr. Jennifer Couch (Moderator), NIH NCI

TRACK B

Dr. Brad Bower (Moderator),NIH NIBIB
Dr. Deborah Duran (Moderator), NIH NIMHD

TRACK C

Dr. Haluk Resat (Moderator), NIH OD
Dr. Tamara Litwin (Moderator), NIH OD
12:10-12:20pm ET
BREAK
12:20pm-1:20pm ET
BREAKOUT SESSION 6
During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects.

TRACK A

Dr. Keith Feldman (Moderator), Assistant Professor, Children's Mercy Kansas City
Consideration of Geospatial Distribution in the Measurement of Study Cohort Representativeness and Data Quality
Download Slides Dr. Cole Vonder Haar, Assistant Professor, Ohio State University
Behavioral Phenotyping of Risky Decision-Making After TBI in a Rat Model Enables Evaluation of Statistical Methodology
Download Slides Dr. Pilhwa Lee, Lecturer, Morgan State University
Algorithmic Bias in Single Cell Analysis: A Study of Optimal Transport and Sinkhorn Divergence
Download Slides Dr. Evelyn Hsieh, Associate Professor of Medicine/Chief of Rheumatology, Yale School of Medicine/VA Connecticut Healthcare System; Mr. Dax Westerman, Senior Data Scientist, Vanderbilt University Medical School
Enabling Al/ML-Readiness of Data from Dual-Energy X-ray Absorptiometry (DXA) Images via Optical Character Recognition (OCR) and Deep Learning
Download Slides TRACK B

Dr. Mark Musen (Moderator), Professor, Stanford University
Metadata for the Masses: Making CEDAR Portable and Cloud-Based
Download Slides Dr. Matteo D'Antonio, Assistant Professor, UC San Diego
Using Ancestry-Agnostic Approaches for Genome-Wide Association Studies and Polygenic Risk Scores
Download Slides Dr. James Anderson, Senior Software Design Engineer, University of Utah - Moran Eye Center
Retinal Circuitry - Improving AI Readiness of Existing Retinal Connectomes
Download Slides Dr. Ron Alkalay, Associate Professor in Orthopedic Surgery, Beth Israel Deaconess Medical Center
Application of AI/ML Models for Musculoskeletal Spine Research in Patients with Metastatic Spinal Disease: Successes and Challenges.
Download Slides Ms. Jessica Gjonaj, Research Coordinator, NYU Grossman School of Medicine
NYU-Moi Data Science for Social Determinants Training Program
Download Slides
1:20-1:30pm ET
BREAK
1:30-2:30pm ET
BREAKOUT SESSION 7
During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects.

TRACK A

Professor Stephanie Kraft (Moderator), Assistant Professor, Seattle Children's Research Institute
Advancing Equity in AI-Enabled Mobile Health Tools: Community-Informed Design Considerations
Download Slides Dr. Shigang Chen, Professor, University of Florida
Making Parkinson's Disease Data AI-Ready for Cloud-Outsourced Machine Learning Research with Differential Privacy
Download Slides Dr. David Linden, Associate Professor of Physiology, Mayo Clinic
Developing Computational Tools to Analyze the Structure of Nerve Cells in the Bowel to Better Understand Digestive Disease
Download Slides Ms. Deepa Krishnaswamy, Instructor in Radiology, Brigham and Women's Hospital
Generation and Dissemination of Enhanced AI/ML-ready Prostate Cancer Imaging Datasets for Public Use
Download Slides TRACK B

Dr. Zhe Sage Chen (Moderator), Associate Professor, New York University Grossman School of Medicine
Generative AI for Interictal EEG-Based SUDEP Risk Assessment

Dr. Kristin Kostick-Quenet, Assistant Professor, Baylor College of Medicine
Patient-Centric Federated Learning: Automating Meaningful Consent to Health Data Sharing with Smart Contracts
Download Slides Dr. Thomas Hampton, Research Scientist, Geisel School of Medicine at Dartmouth
RESPIRE: A Reusable Architecture for Domain Centric ‘Omics Data Sharing
Download Slides Dr. Tanvi Bhatt, Professor, University of Illinois at Chicago
WalkVIZ: Development of a Comprehensive Tool to Process and Visually Analyze Gait Data
Download Slides
2:30-2:40pm ET
BREAK
2:40-3:40pm ET
BREAKOUT SESSION 8
During this breakout session, participants from the FY22 NOT-OD-22-065 and NOT-OD-22-067 programs will give 10-minute lightning presentations that discuss the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects. Participants from the FY23 NOT-OD-23-082 program will give 10-minute lightning presentations on their project motivation, plan, and expected outcome.

TRACK A

Dr. Yanbin Yin (Moderator), Professor, University of Nebraska Lincoln
AI/ML Ready Carbohydrate Enzyme Gene Clusters in Human Gut Microbiome
Download Slides Dr. Tezcan Ozrazgat Baslanti, Research Associate Professor, University of Florida
AI/ML Ready Data Enriched with Social Determinants of Health and Unstructured Text Data for Acute Kidney Injury Risk Prediction
Download Slides Dr. Xiaoqian Jiang, Professor and Chair, University of Texas Health Science Center at Houston
Ethically Optimize Machine Learning Models with Real-World Data to Improve Algorithmic Fairness
Download Slides Mr. Seha Ay, Graduate Student, Wake Forest School of Medicine
Applying Gerchberg-Saxton Algorithm on Biomedical Data to Mitigate Sampling Bias on Under-Represented Populations
Download Slides TRACK B

Dr. David Gutman (Moderator), Associate Professor, Emory University
Piloting a Web-Based Neuropathology Image Resource for the ADRC Community: The Brain Digital Slide Archive
Download Slides Dr. Andre Holder, Assistant Professor, Emory University
Battling Bias in Sepsis Prediction: Towards an Informed Understanding of EMR Data and Its Limitations
Download Slides Dr. Vida Abedi, Associate Professor, Penn State University
Enhancing Imputation for Clinical Trials: The Path for a Flexible Toolkit
Download Slides Dr. Vibhuti Gupta, Assistant Professor, School of Applied Computational Sciences, Meharry Medical College
AI/ML ready mHealth and wearables data for Dyadic HCT
Download Slides
3:40-3:50pm ET
BREAK
3:50-4:30pm ET
BREAKOUT SESSION 5 REPORT BACK

This session brings participants back together to see which AI barriers, challenges, and opportunities (discussed in the virtual rooms during Breakout Session 5) are the most prevalent/promising among peers.


Ms. Christine Cutillo, NIH ODSS
Dr. Jennifer Couch, NIH NCI
Dr. Brad Bower, NIH NIBIB
Dr. Deborah Duran, NIH NIMHD
Dr. Haluk Resat, NIH OD
Dr. Tamara Litwin, NIH OD
4:30-4:50pm ET
END OF THE MEETING POLL
The poll provides participants with the opportunity to give their feedback and enhance NIH AI activities.
Ms. Christine Cutillo, Health Data Scientist for AI Ethics, NIH ODSS
Download Slides
4:50-5pm ET
CLOSEOUT & ADJOURN
Ms. Christine Cutillo, Health Data Scientist for AI Ethics, NIH ODSS

Call for Speakers and Registration

Register below if you are involved in the AI supplement programs.