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Nicoleta Economou-Zavlanos

Assistant Professor of Biostatistics & Bioinformatics
Biostatistics & Bioinformatics, Division of Translational Biomedical
2424 Erwin Road, Room 9042, Durham, NC 27705

Overview


Director of Duke Health AI Evaluation and Governance  
Founding Director of Algorithm-Based Clinical Decision Support (ABCDS) Oversight 

Nicoleta Economou-Zavlanos, PhD, is the Director of the Duke Health AI Evaluation & Governance Program and the founding director of the Algorithm-Based Clinical Decision Support (ABCDS) Oversight initiative. In this capacity, she leads Duke Health’s efforts to evaluate and govern health AI technologies. Dr. Economou also serves on the Executive Committee of the NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) Program. Additionally, she served as Scientific Advisor for the Coalition for Health AI (CHAI), driving the development of guidelines for AI assurance in healthcare, from 2024 to 2025. 

A nationally recognized expert in health AI governance, Dr. Economou has been instrumental in creating frameworks and methodologies for the registration, review, and assurance of health AI systems. Her research, published in leading journals such as NPJ Digital MedicineJAMAJAMA Health Forum, and JAMIA, reflects her commitment to advancing the responsible development and use of AI in healthcare.

Current Appointments & Affiliations


Assistant Professor of Biostatistics & Bioinformatics · 2024 - Present Biostatistics & Bioinformatics, Division of Translational Biomedical, Biostatistics & Bioinformatics

In the News


Published June 16, 2025
Charting a Future With AI
Published May 24, 2024
Local health leaders discuss making trustworthy AI a reality
Published January 2, 2024
Top Health IT Analytics Predictions, Priorities for This Year

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Recent Publications


A federated learning framework for ethical dynamic treatment allocation across heterogeneous hospitals.

Journal Article J Biomed Inform · February 2026 OBJECTIVE: In this paper, we propose an adaptive federated learning framework to learn optimal treatments for individual hospitals that possibly serve different patient populations. The proposed framework can enable the design of more efficient treatment a ... Full text Link to item Cite
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Recent Grants


Measuring AI Maturity in Healthcare Organizations

ResearchPrincipal Investigator · Awarded by Vanderbilt University Medical Center · 2023 - 2026

Health AI Coalition Workgroup

ResearchProject Lead · Awarded by Mitre Corporation · 2022 - 2022

Enhanced X-ray Angiography Analysis and Interpretation Using Deep Learning

ResearchProgram Manager · Awarded by Vigilant Medical · 2019 - 2022

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Education


Drexel University · 2012 Ph.D.