Abstract Amyotrophic Lateral Sclerosis (ALS) is a rapidly progressive neurodegenerative
disease. Accurately predicting the survival time for ALS patients can help patients and …

Survival analysis is widely employed across medicine, business, and the social sciences.
However, the absence of a unified and standardized software solution for evaluating survival …

Simple Summary Traditional survival models estimate risk across many patients, and thus,
translating survival outcomes to individual patients is a difficult task. Individual survival …

Variational Inference (VI) is a commonly used technique for approximate Bayesian inference
and uncertainty estimation in deep learning models, yet it comes at a computational cost, as …

Predicting future events always comes with uncertainty, but traditional non-Bayesian
methods cannot distinguish certain from uncertain predictions or explain the confidence in …

Discrimination and calibration represent two important properties of survival analysis, with
the former assessing the model's ability to accurately rank subjects and the latter evaluating …

Predicting the remaining useful life (RUL) of ball bearings plays an important role in
predictive maintenance. A common definition of the RUL is the time until a bearing is no …

As cancer is the leading global cause of death, an ongoing challenge is predicting an
individual's cancer progression accurately, to facilitate personalized treatment planning …

Background: As cancer is the leading global cause of death, an ongoing challenge is
predicting an individual's cancer progression accurately, to facilitate personalized treatment …

The rate of 30-day hospital readmission is a common measurement of hospital quality,
which can affect the funding a hospital receives. Over a quarter of readmissions are …