recommendation system for eCommerce healthcare portal suggestion
Your recommendation system will be designed to tell the customer what product they should choose, however, this doesn't account for what products the customer likes.  A ML method could take all the input parameters from the recommendation system and provide a recommended product based on what similar users liked.

There's no specific ML technique for considering HIPPA constraints.  This would come into play more in the pre-processing stage.  For example, you might not be able to acquire specific birth dates and addresses, but maybe you can get an age range and a zip code (first 3 digits only).

Logistic regression is frequently used in healthcare for binary classification.

There are lots of tutorials online for building ML models.  Kaggle has a good tutorial for Python and R using titanic survival data.