Upcoming Events

Bio: Dr. Hernandez-Boussard is an Associate Dean of Research and Professor of Medicine (Biomedical Informatics), Biomedical Data Sciences, Surgery and Epidemiology & Population Health (by courtesy) at Stanford University. With a rich background and vast expertise in biomedical informatics, health services research, and epidemiology, she is at the forefront of advancing healthcare through the development, evaluation and application of innovative methods. Through her research, she aims to effectively monitor, measure, and predict equitable healthcare outcomes. By leveraging real-world data, her team works diligently to construct a solid body of evidence that can significantly enhance patient outcomes, streamline healthcare delivery, and provide valuable guidance for health policy decisions. In addition, Dr. Hernandez-Boussard focuses intensively on mitigating bias and enhancing equity within artificial intelligence applications in healthcare settings. Through her research and evaluation of AI technology, she seeks to advance healthcare practices while ensuring that diverse populations receive equitable resources, care, and outcomes. ZOOM ID: 817 5305 8557

Bio: Dr. Satrajit Ghosh is the Director of Open Data in Neuroscience Initiative and a Principal Research Scientist at the McGovern Institute for Brain Research at MIT, and an Assistant Professor of Otolaryngology - Head and Neck Surgery at Harvard Medical School. He is a computer scientist and computational neuroscientist by training. He directs the Senseable Intelligence Group (https://sensein.group/) whose research portfolio comprises projects on spoken communication, brain imaging, and informatics to address gaps in scientific knowledge in three areas: the neural basis and translational applications of human spoken communication, machine learning approaches to precision psychiatry and medicine, and preserving information for reproducible research and knowledge generation. He is a PI on NIH projects supported by the BRAIN Initiative and the Common Fund and is a big proponent of open and collaborative science. ZOOM ID: 817 5305 8557

Have you collected or are interested in collecting accelerometry data acquired from wrist-worn devices, like a smartwatch or fitness tracker in your field study? Are you curious about the re-identification risks such data may or may not pose to your participants? This seminar will focus on increasing your awareness and perceptions of a potential risk to participant privacy from the use of wrist-worn motion sensors like activity trackers or smartwatches - specifically privacy risks associated with re-identification from raw accelerometer data. Using two case studies, we examine how raw accelerometry data can be traced back to individuals, the implications for research participant privacy, and strategies to mitigate risks. Join us for a critical discussion on safeguarding participant privacy in digital health research. Bio:  Dr. Camille Nebeker directs the UC San Diego Research Ethics Program and is a professor of public health with appointments in the UC San Diego Design Lab and the Herbert Wertheim School of Public Health and Human Longevity Science. In 2018, Dr. Nebeker co-founded the ReCODE Health center, which is dedicated to conducting cutting edge research to inform ethical practices in digital/AI health research – including machine learning and the use of large language models. The ReCODE Health center supports education and consultation services to guide ethical practices in technology-supported health research across diverse research sectors including traditional academic research and, increasingly, the health technology sector. She’s a principal investigator with the Bridge2AI Center’s Ethical, Legal and Social Implications Core.  Dr. Santosh Kumar is the Lillian and Morrie Moss Chair of Excellence Professor in the Department of Computer Science at the University of Memphis. He directs the NIH-funded mDOT Center and previously led the NIH-funded MD2K Center of Excellence. He is also co-founder and CEO of CuesHub, PBC. Santosh’s research has resulted in wearable AI for detecting stress, smoking, craving, drug use, brushing, flossing, and stressful conversations from physiological and motion sensors. His team has developed software platforms for  smartphone, smartwatches, and cloud that has been used across the country for collecting hundreds of terabytes of mobile sensor data from over 3,000+ human volunteers in their natural environments as part of various scientific user studies that are being used for understanding privacy risks and developing foundation AI models for wearable sensors. ZOOM ID: 817 5305 8557  

This talk will discuss legal and ethical issues that arise when hospitals implement medical AI, including discussing ambient listening, AI scribing, and AI drafting of communication with patients, as well as more clinical technologies. ZOOM ID: 817 5305 8557 Bio:  Professor Cohen is a leading expert in bioethics, health law, and civil procedure. An elected member of the National Academy of Medicine, he has advised U.S. Vice President Harris on reproductive rights, discussed medical AI policy with the Korean Congress, and lectured globally. His work appears in top legal, medical, and public health journals, as well as major media outlets. A Harvard Law professor since 2008, he has authored over 200 articles and 20 books on topics like AI in medicine, reproductive technologies, and health policy. He also leads major research initiatives, provides expert testimony, and remains active in litigation and bioethics advisory roles. —- Prof. Cohen is one of the world’s leading experts on the intersection of bioethics (sometimes also called “medical ethics”) and the law, as well as health law. He also teaches civil procedure. He is an elected member of the National Academy of Medicine and has advised the U.S. Vice President Harris on reproductive rights, discussed medical AI policy with members of the Korean Congress, and lectured to legal, medical, and industry conferences around the world. His work has been frequently covered by or appeared in media venues such as PBS, NPR, ABC, NBC, CBS, CNN, the New York Times, The Washington Post, the Boston Globe. He was the youngest professor on the faculty at Harvard Law School (tenured or untenured) both when he joined the faculty in 2008 (at age 29) and when he was tenured as a full professor in 2013 (at age 34), though not the youngest in history. Prof. Cohen’s current projects relate to medical AI, mobile health and other health information technologies, abortion, reproduction/reproductive technology, the therapeutic use of psychedelic drugs, research ethics, organ transplantation, rationing in law and medicine, health policy, FDA law, translational medicine, medical tourism and many other topics. He is the author of more than 200 articles and chapters and his award-winning work has appeared in leading legal (including the Stanford, Cornell, and Southern California Law Reviews), medical (including the New England Journal of Medicine, JAMA), bioethics (including the American Journal of Bioethics, the Hastings Center Report), scientific (Science, Cell, Nature Reviews Genetics) and public health (the American Journal of Public Health) journals, as well as Op-Eds in the New York Times, Washington Post, New Republic, Time Magazine, and other venues. Cohen is the author, co-author, editor, or co-editor of more than 20 books. They include: COVID-19 and the Law (Cambridge University Press, 2023); Reproductive Technologies and the Law (Caroline Academic Press, 2022);The Future of Medical Device Regulation (Cambridge University Press, 2022) Consumer Genetic Technologies: Ethical and Legal Considerations (Cambridge University Press, 2021); Readings in Comparative Health Law and Bioethics (Carolina Academic Press, 2020); Disability, Health, Law, and Bioethics (Cambridge University Press, 2020); Transparency in Health and Health Care in the United States (Cambridge University Press, 2019); Health Care Law and Ethics (Aspen, 2018); Big Data, Health Law, and Bioethics (Cambridge University Press, 2018); Law, Religion, and Health in the United States (Cambridge University Press, 2017); Specimen Science (MIT Press, 2017); Nudging Health: Health Law and Behavioral Economics (John Hopkins University Press, 2016) The Oxford Handbook of U.S. Health Care Law (Oxford University Press, 2016); FDA in the Twenty-First Century: The Challenges of Regulating Drugs and New Technologies (Columbia University Press, 2015); Patients with Passports: Medical Tourism, Law, and Ethics (Oxford University Press, 2014); Human Subjects Research Regulation: Perspectives on the Future (MIT Press, 2014); The Globalization of Health Care: Legal and Ethical Issues (Oxford University Press, 2013). For his law school teaching he was awarded the HLS Student Government Teaching and Advising Award in 2017. For the public he created the free online Harvard X class Bioethics: The Law, Medicine, and Ethics of Reproductive Technologies and Genetics, taken by more than 100,000 students. You can also watch his Tedx talk, Are There Non-Human Persons? Are There Non-Person Humans? He is also the faculty lead on Zero-L, an online course to help law students transition to law school that has been used by more than half of all U.S. law schools. Prior to becoming a professor he served as a law clerk to Judge Michael Boudin of the U.S. Court of Appeals for the First Circuit and as a lawyer for U.S. Department of Justice, Civil Division, Appellate Staff, where he handled litigation in the Courts of Appeals and (in conjunction with the Solicitor General’s Office) in the U.S. Supreme Court. In his spare time (where he can find any!) he still litigates, having authored an amicus brief in the U.S. Supreme Court for in AMP v. Myriad, concerning whether human genes are patent eligible subject matter, a brief that was extensively discussed by the Justices at oral argument. Most recently he has helped with amicus briefs regarding mifepristone (for medical abortion) and gender-affirming care for trans minors. He also provides expert testimony in health law and bioethics litigation. Cohen was selected as a Radcliffe Institute Fellow for the 2012-2013 year and by the Greenwall Foundation to receive a Faculty Scholar Award in Bioethics. He is also a Fellow at the Hastings Center, the leading bioethics think tank in the United States as well as being a fellow of the Pierre Elliot Trudeau Foundation. He leads the Project on Precision Medicine, Artificial Intelligence, and the Law (PMAIL), which is part of the larger Centre for Advanced Studies in Biomedical Innovation Law (CeBIL). He is also the principal investigator for Diagnosing in the Home: The Ethical, Legal, and Regulatory Challenges and Opportunities of Digital Home Health and the Project on Psychedelics Law and Regulation (POPLAR). He previously served as the co-lead on the Regulatory Foundations, Ethics, and Law Program of Harvard Catalyst and as one of the key co-investigators on the multi-million dollar Football Players Health Study

REGISTRATION IS OPEN FOR THE 2025 VOICE AI SYMPOSIUM + HACKATHON SUBMIT ABSTRACTS BY DECEMBER 15TH DISCOUNTED REGISTRATION FOR B2AI MEMBERS (see below for details) We’re excited to invite you to the 2025 Voice AI Symposium and Hackathon, presented by the NIH Common Fund’s Bridge2AI-Voice consortium! From April 22-24 in Tampa, this unique three-day event will bring together researchers, patients, clinician-scientists and top minds in artificial intelligence, bioethics, voice biomarkers, and transformative healthcare for an innovative and interactive hands-on experience. 2025 Voice AI Symposium + Hackathon When: April 22-23 (Symposium) + Apri 24 (Hackathon) Where: Sunny Tampa Florida! At the J.W. Marriott and the Morsani College of Medicine, Taneja College of Pharmacy and Heart Institute, Water Street HIGHLIGHTS FROM LAST YEAR Why Attend? Our theme this year, "Translating AI Research into Reality: Implementing Voice Biomarkers for Transformative Healthcare", will spotlight the real-world applications and ethical considerations of voice AI in healthcare. The symposium will feature prominent industry leaders and renowned bioethics experts, providing a valuable platform for interdisciplinary discussion and learning. Last year, we welcomed speakers from Google, Microsoft, Canary Speech, Sonde Health, Redenlab, NIH, and numerous international startups. Highlights of the Symposium: Interactive Panel Discussions: Engage with leaders and experts on the future of voice AI in healthcare, including ethical considerations and practical applications. Deep Dive Workshops: Hands-on sessions designed to deepen your understanding and skill set in AI and voice biomarkers. Tech Fair: A showcase of the latest tools and innovations in the field, allowing you to explore cutting-edge technologies up close. Hackathon: A full day dedicated to solving real-world healthcare challenges alongside other participants, fostering collaboration and innovation. Poster Competition: A fantastic opportunity for researchers to present their work, share insights, and receive valuable feedback from peers and experts. Networking Event: Connect with professionals across academia, industry, healthcare, and patient advocacy. This is your chance to build valuable connections and explore collaborative opportunities. Secure your place today and join us in Tampa for an unforgettable experience at the forefront of AI and healthcare. B2AI members receive $100 off the cost of registration with the following code: B2AIdiscount! Register Now:  https://www.eventsquid.com/register/26215 Submit Abstracts: https://www.eventsquid.com/register/26217 We look forward to seeing you in April! Warm regards, Jamie Toghranegar   Jamie Toghranegar, SLPD, CCC-SLP, CBIS Research Project Manager, Bridge2AI Voice Speech Language Pathologist USF Health Morsani College of Medicine University of South Florida 12901 Bruce B. Downs Blvd. Tampa, FL 33612

The Opportunity and A Call to Action We are excited to announce the launch of the CM4AI Graph Community Detection competition on Kaggle!  Participating in this challenge will give you a unique opportunity to be part of groundbreaking advancements in biomedical research as part of the Cell Maps for AI (CM4AI) initiative. Challenge Dates: May 14, 2025 – July 31, 2025 Join the Frontier of Biomedical AI Research! The Bridge2AI Functional Genomics Grand Challenge (Cell Maps for AI/CM4AI) is pleased to announce our Kaggle competition focused on using the data and tools generated by CM4AI and leveraging emerging AI/ML methods, such as graph and quantum machine learning, to advance biomedical science and precision medicine. Competition Overview The goal of this competition is to develop methods that identify communities within biological networks to uncover hidden structures and provide new insights into biological systems. By participating, you will help push the boundaries of AI/ ML applications in the life sciences. Why Participate? Shape the Future of Science: Successful approaches can redefine how we understand cellular systems, paving the way for innovative therapeutic strategies for cancer and other human disease. Challenge Yourself: Engage in solving a cutting-edge problem that bridges the gap between AI/ML and molecular biology. Be Part of a Global Community: Collaborate and compete with experts, researchers, and enthusiasts from diverse fields with mentorship from CM4AI investigators.  Key Details CM4AI Resources: https://cm4ai.org and https://youtube.com/@CM4AI Competition Link: https://www.kaggle.com/t/b25c9b18a199411892011bfb88680cf3 Objective: Detect and identify communities from CM4AI SEC-MS data, contributing to the Cell Maps for AI initiative. Who Should Join? This competition is open to anyone passionate about artificial intelligence/machine learning, computational biology, or biomedical research. Whether you're a seasoned expert or an enthusiastic beginner, your contributions can help drive the next wave of discoveries. Don’t miss this opportunity to be part of a transformative journey at the intersection of AI and molecular biology! Join the Challenge Now

All Hands Conference Our May 2025 All Hands Conference will be an opportunity for researchers and experts to engage in vibrant discussions. The NIH Common Fund's Bridge to Artificial Intelligence (Bridge2Al) program will propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (Al) that tackles complex biomedical challenges beyond human intuition. The biomedical research community generates a wealth of data, but most of these data are not suitable for machine learning because they are incomplete. By bringing technological and biomedical experts together with social scientists and humanists, the Bridge2Al program will help bring solutions to this deficit. Open House The Bridge2Al Open House will focus on collaborative approaches, learn about current considerations, explore new datasets, and discuss other key issues related to bridging the gap from biomedical information to Al. Sessions will be centered around the activities of the Bridge2Al Data Generation Projects, which stemmed from Grand Challenges put forth by the National Institutes of Health (NIH). 📋 Check out Digital Program

Join us for the second annual Bridge2AI Open House on Thursday, May 22, 2025, in Rockville, MD! This event provides an amazing opportunity for scientists, ethicists, coders, community members, and practitioners with diverse expertise and experience levels to come together to build unique solutions that will help solve a range of relevant problems. The Bridge2AI Open House will focus on key issues related to bridging the gap from biomedical information to AI. Sessions will be centered around the activities of the Bridge2AI Data Generation Projects, which stem from the National Institutes of Health’s (NIH) Grand Challenges. Register By: May 16, 2025 Register Here

Introduction Fundus imaging is an indispensable tool in primary care for the early detection of major ophthalmic diseases—such as diabetic retinopathy and glaucoma—and for guiding treatment decisions. By noninvasively visualizing the retinal vasculature and subtle changes at the optic nerve head, fundus exams also serve as indicators of systemic health, making them a first line of patient management. With the widespread adoption of high-resolution, digital camera–based fundus imaging, a variety of imaging modalities have rapidly entered clinical practice. Recently, deep-learning–based models for classifying fundus diseases have demonstrated high sensitivity and specificity and have proven their clinical utility by being integrated into numerous software medical devices (SaMD). For example, automated diabetic retinopathy screening systems and glaucoma-progression monitoring tools are already commercially available, contributing broadly to diagnostic support and patient screening. However, most models are trained and validated on data from a single camera type, which limits their performance when applied to images from new or infrequently used devices. To overcome these practical constraints, this challenge aims to develop AI models that deliver consistent diagnostic performance across diverse camera environments. Through the Multi-Camera Robust Diagnosis of Fundus Diseases (MuCaRD) challenge, we will evaluate both robust classification algorithms that generalize to unseen devices and adaptive learning techniques that can quickly fine-tune using only a few sample images from a new camera. Challenge Description Overview: The MuCaRD challenge addresses a critical gap in AI‐driven fundus screening: ensuring consistent performance across both familiar and unseen camera systems. Participants will develop and benchmark models under realistic constraints—training on a limited set of images from one device and then evaluating robustness and adaptability on entirely new devices. By simulating clinical and commercial deployment scenarios, MuCaRD promotes methods that generalize beyond a single data source and can quickly fine‐tune to novel imaging hardware. Tasks: Task 1: Zero-Shot Classification Train on fundus images from a single camera and evaluate on completely unseen devices. Participants perform two separate binary classifiers (glaucoma vs. normal, and referable DR vs. non-referable), submitting full model code and weights to the CodaLab platform. A hidden validation set (200 images each from Optomed Aurora, Mediworks FC162, Optos Ultra Wide, Canon CR2) and a similarly‐sized test set ensure no data leakage. Task 2: Few-Shot Test-Time Adaptation Extend Task 1 by leveraging a small support set (5 labeled images per new camera: 1 positive, 4 negative) provided online during validation and test phases. Models should demonstrate on-the-fly adaptation within a 10 s/image inference limit, showcasing both robustness and efficient fine-tuning. Datasets: AI-READI dataset: A rigorously curated set of high-resolution color fundus images acquired on Optomed Aurora and Eidon cameras across three Bridge2AI partner sites (UAB, UCSD, UW). Images span all four type 2 diabetes severity categories and include expert-verified annotations for diabetic retinopathy stage, image quality scores, and linked clinical metadata (age, sex, HbA1c, blood pressure, comorbidities). This cohort is optimized to benchmark zero-shot model performance and cross-device generalization. Mediwhale Collection: Training from one CR2 and testing images from 5 different cameras. Evaluation & Metrics: Performance is measured by the average of the Area Under the ROC Curve (AUROC) and the Area Under the Precision–Recall Curve (AUPRC) for each disease. To mirror clinical feasibility, all inference and adaptation steps must complete within 10 seconds per image, though this limit does not directly penalize the score. Submissions are limited to two runs per day during validation to curtail leaderboard overfitting. Important Dates Training Release: June 30, 2025 Validation Submission: June 30 – August 15, 2025 Test Submission: August 15 – August 23, 2025 Winner Announcement: August 30, 2025 Workshop: October 6–10, 2025 Awards Certificates will be presented to the top three teams in each task. The first and corresponding authors of the winning teams will be invited to co-author the challenge summary paper and to present their results at the workshop. Contact For inquiries, please email: g.young@mediwhale.com

Please join us on Tuesday, July 15th, 2025 at 12pm-1pm PST/3pm-4pm EST for the discussion forum: “The Pulse of Ethical Machine Learning in Health",  by Dr. Marzyeh Ghassemi Registration not required!  Additional details in the attached documents and message below. Bio: Dr. Marzyeh Ghassemi is an Associate Professor at MIT in Electrical Engineering and Computer Science (EECS) and Institute for Medical Engineering & Science (IMES). She holds MIT affiliations with the Jameel Clinic, LIDS, IDSS, and CSAIL. For examples of short- and long-form talks Professor Ghassemi has given, see her Forbes lightning talk, and her ICML keynote.  Professor Ghassemi holds a Germeshausen Career Development Professorship, and was named a CIFAR Azrieli Global Scholar and one of MIT Tech Review’s 35 Innovators Under 35. In 2024, she received an NSF CAREER award, and Google Research Scholar Award. Prior to her PhD in Computer Science at MIT, she received an MSc. degree in biomedical engineering from Oxford University as a Marshall Scholar, and B.S. degrees in computer science and electrical engineering as a Goldwater Scholar at New Mexico State University.  Professor Ghassemi’s work spans computer science and clinical venues, including NeurIPS, KDD, AAAI, MLHC, JAMIA, JMIR, JMLR, AMIA-CRI, Nature Medicine, Nature Translational Psychiatry, and Critical Care. Her work has been featured in popular press such as MIT News, The Boston Globe, and The Huffington Post.