A health care foundation model built by Amalgam Rx and shaped by researchers at the University of Miami Miller School of Medicine has won "Overall Large Language Model of the Year" at the 2026 AI Breakthrough Awards. The global competition drew more than 5,000 nominations from over 20 countries, and the award places Chiron alongside past winners such as NVIDIA, Qualcomm and Snowflake.
Azizi Seixas, Ph.D., professor of psychiatry and behavioral sciences and interim chair of the Department of Informatics and Health Data Science at the Miller School, led the effort to identify how the technology can be applied in real-world clinical settings. His work focuses on translating AI's potential into tools that improve patient care.
"The partnership between Amalgam and The Media and Innovation Lab represents a shared vision to shape the future of medical-grade artificial intelligence and learning health systems," Dr. Seixas said. "Together, we are working to ensure that next-generation AI moves beyond technological innovation to become safely integrated into routine clinical care, where it can improve decision-making, personalize treatment and enhance patient outcomes."
Understanding the complete patient journey
Chiron is a health care-specific large language model designed to analyze a patient's entire medical history rather than isolated encounters. It interprets diagnoses, medications, lab results, referrals, comorbidities and other longitudinal data simultaneously. By tracking how those events unfold over time, the model identifies patterns that may signal emerging health risks or opportunities for earlier intervention.
"Chiron is designed to understand the complete clinical journey of a patient rather than isolated health care encounters," Dr. Seixas said. "What makes Chiron unique is its ability to synthesize complex health care data into meaningful clinical reasoning while operating within the realities of health care delivery."
The model's design reflects a core truth of medicine: health care decisions are rarely based on a single encounter. Researchers working in AI for Healthcare often stress that clinical data must be interpreted longitudinally to surface hidden patterns. By treating each diagnosis, medication change, and hospitalization as part of a connected narrative, Chiron can help clinicians detect disease earlier, identify high-risk patients, and personalize treatment decisions.
Bridging innovation and implementation
A central part of Dr. Seixas's involvement has been ensuring the technology integrates into health care environments in ways that support clinicians and patients. His background as an implementation scientist and digital health researcher guided the focus on sustainable clinical practice.
The partnership's initial use case targeted sleep apnea. Alberto Ramos, M.D., professor of neurology and research director of the sleep program at the Miller School, contributed to the project. "This approach can help examine a very common but often overlooked disorder that affects brain, cardiovascular and metabolic health over time," Dr. Ramos said. "AI that can recognize these longitudinal patterns has the potential to help clinicians identify high-risk patients earlier and deliver more personalized care."
Researchers are now exploring additional applications, including disease detection and clinical decision support within academic health environments. Any future implementation will undergo rigorous scientific evaluation and institutional oversight.
A vision for the future of medicine
For Dr. Seixas, the award underscores the importance of collaboration between academia and industry. Academic medical centers contribute scientific rigor, clinical expertise, and implementation science, while technology companies bring engineering strength and scalable product development. That combination accelerates the balanced adoption of new technologies.
"At the University of Miami Miller School of Medicine, we believe the future of health care will be defined by learning health systems powered by medical-grade AI," Dr. Seixas said. "Partnerships like this are essential because they allow us to responsibly develop, validate and implement these technologies while educating the next generation of clinician-innovators, scientists and engineers who will lead the future of medicine."
Why this matters for Science and Research
The Chiron collaboration illustrates how AI for Science & Research moves from promising technology to clinically validated tools. For researchers, the award signals that rigorous implementation science-not just model performance-is becoming a key differentiator. Academic medical centers are building the frameworks to evaluate, deploy, and continuously improve AI-powered tools within health systems. This partnership offers a concrete model for how translational research can bridge the gap between algorithm development and patient impact, with scientific oversight at every step.
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