John Snow Labs - Healthcare NLP Libraries are designed to help organizations extract insights from unstructured documents and enable faster, more accurate data analysis. Healthcare NLP is a cutting-edge natural language processing solution designed specifically for the healthcare domain, leveraging advanced machine learning algorithms and a vast medical knowledge base. Healthcare NLP excels in transforming raw healthcare data into structured, actionable information.

About the offer

This product includes a package of Natural Language Processing Python libraries specific for the Healthcare domain. It allows quick and easy text annotation with pre-trained DL models, rules, and prompts but also NLP model testing, training, and tuning. The product guarantees state-of-the-art accuracy, native scalability, optimizations for the latest hardware, and the ability to easily compose text and image processing pipelines.

There is no limit on the number of documents, models, or pipelines that can be used with this subscription: the software is licensed on a per-server basis.

What is included

• Spark NLP, the most widely used NLP library in the Enterprise. It provides production-grade, scalable, and trainable versions of the latest research in natural language processing and 10,000+ pre-trained models and pipelines covering tasks such as Entity Recognition, Information Extraction, Spelling and Grammar, Text Classification, Translation, Summarization, Question Answering or Emotion Detection.
• Healthcare NLP software and models, enabling clinical and biomedical Named Entity Recognition for 400+ entity types, assertion status detection (identify between positive, negative, possible, past, and future facts), clinical relation extraction, clinical entity resolution to SNOMED-CT, ICD-10, CPT, RxNorm, LOINC, NDC, ICD-I, MeSH, UMLS.
• Visual NLP (OCR) software and models, enabling form understanding, table detection and extraction, noisy image enhancement, visual document classification, visual entity recognition, signature detection, and image de-identification.
• Full access to all models and pipelines published on the NLP Models Hub (currently 1,200+ healthcare-specific models and 17,500+ general models).
• 30+ Ready-to-use Jupyter notebooks that will help you get started with text and image analysis on all major NLP tasks such as text classification, sentiment analysis, named entity recognition, relation extraction, assertion status, entity linking, de-identification, translation, summarization, question answering, spelling and grammar.
• NLU python library for text understanding that can be used to test models and pipelines with one line of code.
• Spark NLP Display library for out-of-the-box annotation display on top of textual content.

• Teams of Python developers that need to extract entities and relations from text, image, and pdf documents;
• Data scientists who deal with NLP problems;
• Machine learning engineers who need to test/train/tune NLP models;
• Scientific researcher groups who need to extract meaning from unstructured, natural language documents;
• Anyone else interested in text and image analysis, image digitization, data extraction, document labeling, and/or NLP model training.

• Recommended memory: 32GB RAM
• Recommended vCPU:8 vCPUs
• Operating System:Ubuntu 20.04

• Jupyter Lab preinstalled and available at http://IP_ADDRESS/jupyter. The password to login to Jupyter Lab is the INSTANCE_ID

1. Subscribe to the product on the AWS Marketplace.
2. Deploy it on a new machine.
3. Access the welcome page for a guided experience on http://IP_ADDRESS