The digital revolution is changing our world. Digital devices, sensors and technologies are able to collect large multimodal datasets containing bio, social and lifestyle information. Such large complex bodies of health data, in combination with recent advances in artificial intelligence (AI), hold enormous potential for health research. This research group aims to develop causal inference and AI methods to model, predict and explain the development of diseases over the life course using high-dimensional data. To this end, we will use sensitive data sources in compliance with ethical and data protection conditions to extract relevant knowledge, advance deep learning models and generate causal insights - ultimately helping to uncover the causes of complex diseases and optimize prevention strategies.

Funded by the Deutsche Forschungsgemeinschaft (DFG)

Lifespan AI

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Lifespan AI

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