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Emese Katalin Vágó is a Biostatistician at Aarhus University. Her research primarily focuses on clinical epidemiology, leveraging statistical machine learning methods. She plays a key role in conducting epidemiological register-based studies, often collaborating with international research institutes. Over the years, she has contributed to various research outputs, with an increasing number of projects planned for the coming years. Her work aligns with contemporary statistical practices in epidemiology, emphasizing robust and reproducible science. Emese is dedicated to advancing the understanding of health data through sophisticated analytical techniques, aiming to improve public health outcomes. Her expertise spans across multiple domains, making her a vital member of academic and research collaborations. Emese is actively engaged in research that involves innovative statistical approaches to tackle complex health issues, ensuring that her methodologies are informed by the latest advancements in the field.
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