Detect anatomical references
Automatically identify Anatomical System, Cell, Cellular Component, Anatomical Structure, Immaterial Anatomical Entity, Multi-tissue Structure, Organ, Organism Subdivision, Organism Substance, Pathological Formation in clinical documents using our pretrained Spark NLP model.
Detect demographic information
Automatically identify demographic information such as Date, Doctor, Hospital, ID number, Medical record, Patient, Age, Profession, Organization, State, City, Country, Street, Username, Zip code, Phone number in clinical documents using three of our pretrained Spark NLP models.
Detect tumor characteristics
Automatically identify tumor characteristics such as Anatomical systems, Cancer, Cells, Cellular components, Genes and gene products, Multi-tissue structures, Organs, Organisms, Organism subdivisions, Simple chemicals, Tissues from clinical documents using our pretrained Spark NLP model.
Recognize entities in scanned PDFs
End-to-end example of regular NER pipeline: import scanned images from cloud storage, preprocess them for improving their quality, recognize text using Spark OCR, correct the spelling mistakes for improving OCR results and finally run NER for extracting entities.