A Longitudinal Attribute-Conditioned Neural Network for Modeling Health-State Transition Probabilities in Temporally Irregular Data: The LANTERN Framework

In three linesLANTERN, a longitudinal attribute-conditioned neural network, estimates health-state transition probabilities for irregular temporal data. Tested on Health and Retirement Study, the model outperforms logistic regression and gradient boosting in severe disability and mortality discrimination, with superior calibration and lowest transition matrix error.

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