2024 NIH ODSS AI Supplement Program PI Meeting

Wednesday, March 27, 2024

In 2024, the NIH Office of Data Science Strategy (ODSS) held its second meeting of AI supplement awardees. The meeting was 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 provided a platform for participants to exchange insights on their projects, celebrate accomplishments, discuss best practices, share lessons learned, and engage in collaborative discussions.

Read a report of the meeting.

Attendees

Principal Investigators from the following cloud supplement programs were invited:

NOT-OD-22-065 – FY2022 Request for ODSS Funds to Advance the Ethical Development and Use of AI/ML in Biomedical and Behavioral Sciences (also known as FY22 AI-Ethics program)
NOT-OD-22-067 – FY2022 Request for ODSS Funds to Support Collaborations to Improve the AI/ML Readiness of NIH-Supported Data (also known as FY22 AI-Readiness program)
NOT-OD-23-082 – FY2023 Request for ODSS Funds to Support Collaborations to Improve the AI/ML Readiness of NIH-Supported Data (also known as FY23 AI-Readiness program)

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

2024 NIH ODSS AI Supplement Program PI Meeting
Day 1
Time	Presentation
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 explored 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 gave 10-minute lightning presentations that discussed 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 gave 10-minute lightning presentations that discussed 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 gave 10-minute lightning presentations that discussed 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 gave 10-minute lightning presentations that discussed the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects. Participants from the FY23 NOT-OD-23-082 program gave 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

2024 NIH ODSS AI Supplement Program PI Meeting
Day 2
Time	Presentation
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, gave participants time to discuss AI barriers, challenges, and opportunities (including novel ideas and future directions). 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 gave 10-minute lightning presentations that discussed 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 gave 10-minute lightning presentations that discussed 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 gave 10-minute lightning presentations that discussed the motivation, achievements, best practices, lessons learned, and future plans of their awarded AI projects. Participants from the FY23 NOT-OD-23-082 program gave 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 brought 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 provided 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