Overview
This product is designed to help organizations extract insights from unstructured documents and enable faster, more accurate data analysis. It provides a ready to use Jupyter Hub deploymet that can be used to run John Snow Labs Python library for Healthcare Language Understanding and Visual Language Understanding. The software is designed for data scientists, software developers, and researchers who need to understand unstructured text such as clinical notes, radiology reports, research papers, clinical trial protocols, voice-of-the-patient surveys, lab or sequencing reports - with state-of-the-art accuracy. 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 pay-as-you-go basis. What is included :
- John Snow Labs Healthcare Language Understanding Python library, including access to 2,000+ healthcare-specific models covering common tasks like entity recognition, relation extraction, resolving entities to medical terminologies, de-identification, text summarization, question answering, spelling & grammar correction, assertion status detection, embedding calculation, and more.
- John Snow Labs Visual Document Understanding Python library, which provides the ability to read PDF, DOCX, DICOM, and various image file formats and automatically extract text, tables, charts, and key-value pairs from forms, using state-of-the-art multimodal models.
- 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.
- Support directly by the data scientists and medical doctors who build the software, as well as access to all new software releases, model updates, and documentation during the subscription period.
Key Features:
- Keep up with the state of the art: With new releases every two weeks, our main commitment is to not only provide you with the best accuracy today, but continuously productize newer and better models as they are invented - so that you are always running the most accurate healthcare-specific AI models in history.
- Extract deeper medical information: Going beyond the standard of extracting symptoms, treatments, drugs, and anatomy, the included models can extract 400+ medical entities from free-text documents. These include specialized models for oncology, radiology, mental health, pathology, public health, social determinants of health, adverse events, risk factors, and more.
- Compose, train, and fine-tune your own models: Compose multiple models into custom pipelines, use transfer learning to train or fine-tune models on your own private data, or use zero-shot learning with prompts, all with a few lines of Python code.
- Pay as you go: Only pay for what you use, making the software cost-effective for projects of all sizes, from small-scale research to enterprise-level deployments. Billing is by CPU/hour, not by token, making the software highly cost-effective for large-scale projects. Who is this product for:
- Python developers who need to understand, summarize, de-identify, or extract information from medical text or visual documents
- Data scientists in healthcare or life science who build NLP, LLM, or Generative AI solutions
- Machine learning engineers who need to train, tune, test, or combine LLM & NLP models
- Researchers who need to extract information from unstructured, natural language documents
- Software teams building production-grade solutions for understanding and harmonizing clinical, biomedical, patient voice, or other medical information that is coming from text or visual forms About the Subscription: By subscribing to the Medical Language Models on Jupyter Hub product, you get access to a preconfigured private Jupyter Hub account containing ready-to-use Jupyter notebooks built for the most popular Healthcare NLP & LLM library in the healthcare and life science industry. You automatically get a pay-as-you-go license key that can be used in the notebooks. You only pay for the time any of the notebooks are running NLP processes, based on the number of processors allocated to your Spark session.
Highlights
- Access to state-of-the-art accuracy models designed specifically for the healthcare domain. Supported tasks include summarization, question answering, 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.
- Support for Visual Document Understanding. Access to software and models that enable form understanding, table detection and extraction, noisy image enhancement, visual document classification, visual entity recognition, signature detection, and image de-identification.
Details
Pricing
Dimension | Cost/unit |
---|---|
Medical model usage for annotation or training, per processor per minute | $0.099 |
OCR, Visual document annotation or training, per processor per minute | $0.099 |
Server usage for running annotation or training pipelines per processor per hour | $0.07 |
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Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Customer reviews
AWS licensing server accessible from other systems
I have been using John Snow Labs' software for more than four years.
This new product is an AWS licensing server giving a fully portable pay-as-you-go license.
You can connect from any system to the licensing server and pay the license for the CPU minutes consumed, including, e.g., from Google colab. The licensing cost will be included in your AWS bill, which is easier to get through procurement.
In terms of features, it includes all that the other software licenses do—you can stay within the Healthcare NLP / Spark NLP and work on the usual pipelines. For me, it is de-identification -> clinical NER extraction -> Assertions -> Clinical coding, plus sometimes relation extractions.