AMIA 2025 Informatics Summit Year In Review
Translational Bioinformatics
Tuesday, March 11, 2025 | 8:30-10:00 am
The Translational Bioinformatics Year-in-Review (TBI Year-in-Review) is an annual presentation given by Nicholas Tatonetti, PhD at the AMIA Summit. The talk reviews trends in the translational bioinformatics (TBI) literature, aiming to provide a snapshot of the current state of the field, recognize innovative work, and identify future opportunities. The review process involves triaging and evaluating papers from relevant journals, scoring them based on criteria like informatics novelty, application importance, and "wow factor." The top-scoring papers are highlighted, organized into themed categories inspired by pop songs, and showcased to reflect advancements in linking biological and clinical entities through informatics methods.
Clinical Research Informatics
Wednesday, March 12 | 8:30-10:00 am
The AMIA Clinical Research Informatics (CRI) Year in Review session at the 2025 Informatics Summit will provide a comprehensive overview of the most impactful advancements and trends in clinical research informatics over the past year. Dr. Laura Wiley will key findings from groundbreaking studies, emerging technologies, and evolving methodologies that are shaping the future of the CRI. Attendees will gain insights into how informatics is driving innovation in clinical trials, real-world evidence generation, data integration, and patient-centered research. This session is designed to equip researchers, practitioners, and stakeholders with the knowledge to harness informatics for more effective and efficient clinical research.
Artificial Intelligence and Data Science
Thursday, March 13, 2025 | 8:00-9:30 am
The AI and Data Science Year In Review is an annual retrospective that highlights the most significant advancements, challenges, and forward-looking trends in Artificial Intelligence (AI) and Data Science within health and biomedical informatics research. This comprehensive overview showcases the collaborative efforts between clinicians, researchers, and technologists, emphasizing innovations in machine learning models, large language models (LLMs), and generative AI (genAI) that have potential to revolutionize patient care, diagnostics, and therapeutic development. It also examines the integration of multimodal data sources and ethical considerations surrounding AI deployment in clinical settings. The review serves as a vital resource for the informatics community, providing insights into the current state of AI and Data Science, identifying gaps in knowledge, and suggesting directions for future research and application in healthcare to improve outcomes and efficiency.
Yuan Luo, PhD, FACMI, FAMIA, FIAHSI
