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2025/12/14
The Hidden Gap in Healthcare AI Adoption
A recent JAMA report estimates AI adoption in U.S. healthcare at 5.9% on average, rising to 8.3% by 2025. However, this figure likely reflects mostly non-clinical and imaging AI, while adoption of clinical AI—especially GenAI—remains near zero due to a lack of real-world clinical evidence. Although GenAI is widely accessible and easy to use, the evidence-generation bottleneck is the key barrier to clinical adoption. Accelerating scalable, real-world evidence generation within Learning Health Systems is essential to realizing GenAI’s promise in healthcare.
2025/12/15
At the Chen Institute’s AI Accelerated Science Symposium on October 28, 2025, ELHS Institute founder Dr. AJ Chen proposed a new vision for Open Clinical AI Science (OCAIS) to accelerate the clinical impact of generative AI. The framework delivers free GenAI-based disease prediction services to clinical teams worldwide, including low-resource settings, enabling large-scale participation in clinical evidence generation. By converging GenAI with task-specific Learning Health System units, this approach aims to shorten evidence-generation timelines from decades to years and help prevent GenAI from repeating past failures in health care innovation.
2025/10/25
Dr. AJ Chen delivered a keynote at the Tsinghua Health AI Summit on converging generative AI (GenAI) and Learning Health Systems (LHS) to improve clinical diagnosis and reduce global health disparities. He presented the ELHS Institute’s ML-enabled LHS framework, supported by Nature- and JAMIA-published studies, showing how GenAI embedded in LHS units can enable scalable, responsible evidence generation and democratize high-standard predictive care worldwide.
