Spark NLP for Research and Education
You have our full support for using Spark NLP for Healthcare, Spark OCR, and the Data Library for open research & teaching projects
You have our full support for using Spark NLP for Healthcare, Spark OCR, and the Data Library for open research & teaching projects
recognitionIngestion & Preparation – train your own or use pre-trained models to extract clinical facts (symptoms, diagnoses, treatments, procedures), drug facts (name, strength, dosage, route, frequency, duration), and biomedical terms (organism, tissue, gene, gene product, chemical, …).
telling between positive assertions (“patient has diabetes”), negative assertions (“no fever”), uncertain assertions (“shows indications of depression”), or assertions about other people (“family history of lung cancer”).
train your own or use pre-trained models to resolve recognized entities to SNOMED-CT, ICD-10-CM, ICD-10-PCS, CPT, or RxNorm.
use pre-trained models to automatically identify relations between entities such as drugs, dosage, duration, frequency, clinical events among many others.
normalize medications, lab results, vital signs, and demographic data – to simplify downstream analysis for extracted clinical information.
Anonymize either structured tables or unstructured free text including all GDPR and HIPAA-required fields as well as and then either remove, mask, or obfuscate PHI.
allows you to accurately transform PDF, DOCX, DICOM, and image files to digital text with built-in algorithms for:
Each dataset goes through 3 levels of quality review
Data is normalized into one unified type system
Data and Metadata
Always up to date
includes over 2,200 expert-curated datasets that are ready to download and use on your academic/research project:
Our company is named after Dr. John Snow – the medical doctor who helped stop the outbreak of cholera in 1854 London by analyzing data.
We exist for the very purpose of empowering many more like him in the 21st century.