Predicting survival time with incomplete data


About the research

How long will a patient live after his or her cancer diagnosis? And how long will a marriage between a new couple last? To make predictions of this so-called 'survival time', the time until an event occurs, researchers use statistical methods to analyze lifetime data. But what if you have an incomplete dataset, because, for example, a cancer patient withdraws before the end of a study? Can you still make accurate predictions? That's what Worku Ewnetu (UHasselt - KU Leuven) is working on. Watch the video to find out more.

Worku Ewnetu
KU Leuven - UHasselt

Self-motivated to learn, grow and excel in Statistics and Biostatistics through real-world problem-solving. Worku Ewnetu has a solid background in statistical modeling and data analysis in medical, clinical, and other socio-economic lifetime events. He is doing a joint PhD project at the University of Hasselt and KU Leuven. His current research focuses on developing more flexible statistical methods to analyse complex data, in particular incomplete lifetime data.

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