Available On-Demand

We encounter artificial intelligence (AI) every day, not just in the media, but in everyday applications like smartphone apps and other technologies. But can AI change our everyday life in the hemostasis lab? What might that look like? What prerequisites are necessary, and what are the pitfalls? Join this webinar where Professor Michael Nagler, deputy director of the Center for Laboratory Medicine at Inselspital University Hospital and an associate professor at the University of Bern, will explore these points.

Key learning objectives

  • Understand how diagnosing and predicting events is a primary function of medicine
  • Understand that artificial intelligence is about prediction and diagnosis
  • Explore how the effective application of AI requires expertise in several critical areas

Who should attend

Hemostaseologists, hematologists, anesthetists, physicians, cardiologists, gyneocologists, scientists, lab heads, lab techs, and students/trainees in biotechnology, biology, and medicine

SelectScience is approved as a provider of continuing education programs in the clinical laboratory sciences by the ASCLS P.A.C.E.® Program.

Dora Wells

Dora Wells

Editorial Team

SelectScience

Dora studied biomedical science at the University of Manchester, UK, and as a member of the editorial team, plays an integral role in helping to shape the content on SelectScience.
Michael Nagler, MD, PhD,

Michael Nagler, MD, PhD,

Deputy Director

Inselspital Bern, Switzerland

As a laboratory specialist, hematologist, and epidemiologist, Prof. Nagler has a wide range of training and expertise. Currently, he is the deputy director of the Center for Laboratory Medicine at Inselspital University Hospital and an associate professor at the University of Bern. The focus of his research is one of the most common clinical questions physicians ask, “What does this laboratory test result mean for the individual patient?” To address this question, he advances diagnostic research methodologies and develops creative decision support tools, specifically diagnostic machine learning algorithms.

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