When machine learning is used to make better black-box prediction models for biomedical questions, the expected useful lifetime of the model is small. You can be sure that a bigger model trained on more data or for more time will come along, and make your model obsolete.

What may be more useful in the long run is to develop techniques that use data to discover biological mechanisms. These discoveries will stay relevant even if the original models used to discover them are replaced by other techniques.