You are building an NLP model that reads short clinical notes, discharge summaries, and referral text, then assigns each note to one diagnostic category. The notes contain abbreviations, shorthand, and overlapping symptoms, so the same wording can point to different diagnoses depending on context. Labels come from historical chart review and are unevenly distributed across classes.
How would you classify clinical text into diagnostic categories?
