Dr. Haoyang Li, postdoctoral associate in population health sciences in the Division of Health Informatics and Artificial Intelligence at Weill Cornell Medicine, has received one year of research funding from the highly competitive AI/Big Data/Enabling Technologies Seed Grant to address coordination challenges in laboratory medicine.
“I am grateful for the support from the AI/Big Data/Enabling Technologies Seed Grant. This award will support the prototype development of LabARIA and help advance the application of agentic AI in clinical laboratory medicine,” said Dr. Li.
LabARIA (Laboratory Agentic Reasoning and Integrative Analytics) is a multi-agent AI framework for clinical laboratory operations and quality management. Laboratory data is critical to supporting diagnosis, treatment, and patient care. However, important data streams, including specimen timestamp quality indicators, critical values, quality control, proficiency testing/external quality assessment, reagent use, and staffing, remain distributed across multiple laboratory and operational systems. Oversight relies largely on retrospective, manual review.
Existing AI approaches in laboratory medicine are often limited to narrow, task-specific applications that operate independently and are rarely integrated into broader laboratory workflows. LabARIA will instead integrate operational, analytical, regulatory, and resource signals into a proactive laboratory intelligence layer designed to continuously improve operations.
Dr. He Sarina Yang, medical director of clinical chemistry and toxicology services and associate director of clinical pathology and laboratory medicine, is a close collaborator and co-investigator on the project.
"I believe laboratory medicine is particularly well suited for the implementation of AI agents, and I hope that advances in cutting-edge agentic AI technologies can help improve laboratory quality and efficiency and ultimately enhance patient care,” said Dr. Yang.
Dr. Li looks forward to exploring the potential impact of this research and sincerely thanks Dr. Fei Wang, associate dean for AI and the Frances and John Loeb Professor of Medical Informatics, for his mentorship and continued support, as well as Dr. Yang for her clinical laboratory expertise and valuable guidance.
- Highlights