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Advances in Learning Health Systems Sciences will return in October 2026! Our Call for Abstracts will open in April-May 2026, followed by registration opening in June.

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Engage in healthcare research collaboration with access to learning opportunities and active partnerships, and take part in shaping a smarter healthcare system.

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Our specialized services provide the foundation you need to develop, implement, and evaluate your research, ensuring meaningful contributions to improving healthcare delivery.

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All of Us Risk Modeling

We are working with data from the All of Us program to develop new methods for risk modeling that are tailored to minority groups.

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Federated Learning Collaborative

We are part of a national community of health data science and AI researchers who are facilitating research collaboration and the development of AI and machine learning healthcare algorithms.

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Evaluation of Interoperable CDS System

The SCALED (Scaling AcceptabLE cDs) approach is adapting a Clinical Decision Support system to deliver preventive guidelines to VTE in patients with traumatic brain injury.

A team of UMN researchers compared manual qualitative analysis with LLM-assisted analysis as part of an effort to identify barriers to recovery after emergency abdominal surgery.

Drs. Rui Zhang and Genevieve Melton-Meaux received funding from the National Science Foundation for an international collaboration to improve AI detection of rare genetic disorders.

Former MN-LHS scholar Dr. Thomas Byrd received CTSI funding to conduct a case study on the implementation of a machine learning model into healthcare practice.

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A project RapidEval supported recently drew to a close, releasing new findings on how frontline teams experience sepsis care delivery across a large academic health system.

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