Is there an NLP corpus that contains common medical terms?
Welcome to the biomedical domain, one of the few domains in NLP where there are too many resources to choose from :)

Data resources:

Medline is a database corpus of 30 millions abstracts.
Each Medline abstract is annotated with Mesh descriptors, Mesh being a structured hierarchy of medical concepts.
PubMed Central (PMC) is a database of around 6 millions full biomedical articles (not only abstracts).
UMLS is a database of millions of medical terms grouped by concept, themselves grouped by semantic type (e.g. disease, gene, etc.)
PubTator is a resource which provides all the Medline and PMC documents fully annotated with a combination of Mesh and other ontologies.


Software tools:

MetaMap is the venerable annotator system which annotates any medical text with UMLS labels.
cTakes is another annotator system which is more specialized with clinical texts.
SciSpacy is a Spacy variant specialized for biomedical text. It can also annotate medical terms with UMLS labels.



I think that's all the main ones that I know of... so far.
From your description it looks to me like you probably just need cTakes or SciSpacy. In case you're going to start working with Medline or PMC, be aware that these datasets are massive (a few hundreds GBs).