SeqRisk: Transformer-augmented latent variable model for improved
survival prediction with longitudinal data
SeqRisk: Transformer-augmented latent variable model for improved
survival prediction with longitudinal data
In healthcare, risk assessment of different patient outcomes has for long time been based on survival analysis, i.e.\ modeling time-to-event associations. However, conventional approaches rely on data from a single time-point, making them suboptimal for fully leveraging longitudinal patient history and capturing temporal regularities. Focusing on clinical real-world data and …