Yes if there are many candidate predictors then unsupervised learning is a great first step.
Regarding the big picture, I don’t find prediction of AD that precedes death to be that meaningful. That’s what competing risk analysis does. I find it much more natural to use multi-state models. See [this](https://cran.r-project.org/web/packages/survival/vignettes/compete.pdf) amazing document by Therneau, Crowson, Atkinson.
Discrete time multistate models are even simpler.
[This survey](https://discourse.datamethods.org/t/clinical-trial-outcomes-interrupted-by-other-outcomes) revealed that most researchers find it impossible to really separate death from nonfatal outcomes anyway.