[D] Why do you think transformers are not much used in ML over EHR (health)?

I have been researching about the SOTA in ML over EHR data ([e.g.](https://arxiv.org/ftp/arxiv/papers/2107/2107.09951.pdf)) and it seems that most of the relevant approaches are based on LSTM or GRU. Nowadays, that sequences are mostly handled by transformers, why do you think that in EHR it is still at this point? I have some possible reasons:

* Transformers generally need lots of data, something that may be difficult in healthcare context (privacy stuff)
* Transformer FC layers may suppose a big drawback …

ehr health machinelearning ml think transformers