What types of entities can each scispaCy model recognize? #550
Description
Hello,
First, thank you for developing and maintaining the scispaCy package — it’s an impressive tool and a valuable contribution to the field of biomedical NLP.
I’m currently experimenting with the en_core_sci_md model, and I would like to better understand what types of entities it is designed to recognize. For example, when testing the following text:
"""
The patient is a 58-year-old male with a history of type 2 diabetes and hypertension.
He presents with chest pain and shortness of breath for the past two hours.
In the emergency room, a troponin test was ordered, which came back elevated.
An urgent coronary angiography was performed, and the patient was started on aspirin and atorvastatin.
He has a known penicillin allergy.
His smoking history is considered a major risk factor.
"""
All the words in bold were the ones that I wanted to extract as entities, but the model only extracted the following:
- patient (ENTITY)
- male (ENTITY)
- history of type 2 diabetes (ENTITY)
- hypertension (ENTITY)
- chest pain (ENTITY)
- shortness of breath (ENTITY)
- hours (ENTITY)
Could you please point me to documentation or resources that describe the entity types covered by this model, so that I can better anticipate what it can and cannot extract?
Thank you very much for your time and for your excellent work on scispaCy!