Handling features with multiple values per instance in Python for Machine Learning model
A possible resource is featuretools, they do feature engineering on data that has many records. Their examples are not from medical cases but I think it should work for you too.
You can also manually build several features. For instance, given a list of abdomcirc, you can compute its:

mean
maximum
minimum
variance
difference from minimum to maximum
last value (if they are sorted by date)
number of unique values

These features would get most of the information of the abdomcirc list, and this should help your modelling.
I wouldn't go for the first approach of giving lists to the algorithm, although it is possible, I think it is a relatively advanced thing and I wouldn't go for it unless the simpler approaches don't work.