How to Build an AI Team In a Health Center: Experience in a LatAm Hospital — Dr. Martina Aineseder

Описание: Recorded live on March 10, 2026, this episode of Segmed’s Bytes of Innovation explores what it really takes to build and operationalize AI inside a healthcare institution.

In this session, Dr. Martina Aineseder — Radiologist and Head of the AI in Health Program at Hospital Italiano de Buenos Aires — shares firsthand experience leading an in-house, multidisciplinary AI team within one of Latin America’s leading healthcare systems. Her talk, “How to Build an AI Team Inside a Health Center: Experience in a Latin American Hospital,” provides a practical look at the strategic, operational, and cultural foundations required to successfully develop and implement AI solutions within clinical environments.

Drawing from real-world experience, Dr. Aineseder explains how hospitals can move beyond simply adopting AI tools to building sustainable internal capabilities that support long-term innovation and meaningful clinical impact.

🔹 Hosted by
Aline Lutz, MD, PhD – VP of RWE and Clinical Insights, Segmed
Martin Willemink, MD, PhD – Chief Scientific Officer & Co-founder, Segmed

🎥 What You’ll Learn
Why some healthcare institutions choose in-house AI development instead of relying solely on commercial solutions
How to design a structured AI development and implementation pathway inside a hospital
Approaches for benchmarking proprietary AI models against commercial tools
The importance of multidisciplinary collaboration between clinicians, data scientists, and engineers
Why workflow integration and user engagement are critical for successful AI adoption in clinical practice

💡 Why This Matters
As AI adoption accelerates across radiology and medical imaging, healthcare institutions face an important decision: buy, build, or combine?
While commercial AI solutions can offer rapid deployment, they are not always optimized for local workflows, patient populations, or institutional priorities. Building internal AI capabilities allows health centers to develop solutions tailored to their own clinical needs, epidemiology, and operational realities.
In this session, Dr. Aineseder shares a structured framework and lessons learned from Hospital Italiano de Buenos Aires, offering a roadmap for organizations seeking to move from experimental AI projects to sustainable, real-world clinical implementation.

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