11th Machine Learning for Healthcare Conference (MLHC) 2026

About This Grant

Project Summary Advances in machine learning and artificial intelligence (AI) are reshaping the landscape of healthcare, offering new opportunities to enhance diagnosis, personalize treatment, optimize clinical workflows, and ultimately im- prove patient outcomes. The Machine Learning for Healthcare (MLHC) Conference is dedicated to accelerating scientific progress in this rapidly evolving field by providing a premier forum for the exchange of ideas, dissemi- nation of cutting-edge research, and development of interdisciplinary collaborations among computer scientists, engineers, clinicians, and healthcare innovators. The 11th Annual MLHC Conference, to be held at Johns Hopkins University in Baltimore, MD, on August 12th – 14th, marks a significant milestone for the community. In celebra- tion of this anniversary, the meeting will highlight state-of-the-art advances in machine learning for healthcare while also placing special emphasis on the challenges and opportunities involved in translating these technolo- gies from research settings to clinical practice. Through its emphasis on biomedical informatics and data science methodologies that make health data and machine learning models more findable, interoperable, reusable, and trustworthy in clinical use, MLHC is directly aligned with the NLM’s mission. Specifically, sessions will focus on methodological innovation, rigorous evaluation, deployment considerations, and pathways toward achieving meaningful, real-world impact at the bedside. Core objectives of the conference are to (1) update attendees on timely developments across the spectrum of AI-driven healthcare research, (2) foster cross-disciplinary commu- nication and collaboration, and (3) strengthen the pipeline of future leaders in the field. A central component of MLHC is its commitment to supporting and engaging students/trainees through opportunities such as free con- ference registration, travel awards, best student paper awards, poster and oral presentation sessions, mentoring events, and training-focused workshops. This application seeks funding to support such trainee participation, en- abling students and early-stage researchers to present their work, attend scientific sessions, and engage directly with experts who are shaping the future of AI in healthcare. Support from NLM through this R13 mechanism, will enhance trainee activities, broadening access, particularly for those with limited travel and professional devel- opment resources. While in the previous years, the conference has mainly sought funding from private entities, this year NIH’s support will be critical in expanding the conference’s capacity to reach graduate students, post- doctoral researchers, and early-career investigators across the country. As the MLHC Conference enters its second decade, this support will ensure that the meeting continues to advance rigorous, reproducible, and clin- ically grounded research while cultivating the next generation of innovators dedicated to improving patient care through machine learning.