Sold by: John Snow LabsÂ
Deployed on AWS
Free Trial
Detects drugs and maps them to the corresponding RxNorm codes and drug classes.
Overview
This model was created to facilitate the accurate mapping of drugs to their corresponding RxNorm codes and related drug classes. It is an essential tool for healthcare professionals and pharmacists, ensuring precise medication identification and categorization, which is crucial for patient safety, medication management, and healthcare interoperability.
IMPORTANT USAGE INFORMATION:
After subscribing to this product and creating a SageMaker endpoint, billing occurs on an HOURLY BASIS for as long as the endpoint is running.
-Charges apply even if the endpoint is idle and not actively processing requests.
-To stop charges, you MUST DELETE the endpoint in your SageMaker console.
-Simply stopping requests will NOT stop billing.
This ensures you are only billed for the time you actively use the service.
Highlights
- **Key Features:** - The model accurately maps brand and generic drug names, to their respective RxNorm codes that provides standardized nomenclature for medications, aiding in clear and consistent drug identification. - The model also identifies the related RxNorm drug class, providing essential information about the pharmacological classification of each medication. This feature is useful for understanding the therapeutic uses and mechanisms of action of different drugs.
- The model can interpret a wide range of drug-related terminology from diverse sources, including electronic health records, prescription data, and pharmacological literature. By providing accurate drug classifications, the model assists healthcare professionals in better understanding drug interactions, contraindications, and appropriate medication regimens, enhancing patient care and safety.
- This model can be used in pharmacy management to simplify medication dispensing and inventory management through the provision of standardized drug information. It can also be used to enhance Electronic Health Records (EHR) systems by incorporating precise drug coding, improving medication reconciliation and clinical decision support. It can assist in healthcare data analytics by facilitating the analysis of medication data for research purposes and the improvement of healthcare quality.
Details
Sold by
Delivery method
Latest version
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free for 15 days according to the free trial terms set by the vendor.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m4.xlarge Inference (Batch) Recommended | Model inference on the ml.m4.xlarge instance type, batch mode | $9.84 |
ml.m4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m4.xlarge instance type, real-time mode | $9.84 |
Vendor refund policy
No refunds are possible.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
This model is designed to map drugs to RxNorm codes and their associated drug classes. It ensures precise drug identification and classification, essential for healthcare providers and pharmacists.
Additional details
Inputs
- Summary
To use this model you need to provide input in one of the following supported formats:
- Single Text Document Provide a single text document as a string. { "text": "Single text document" }
- Array of Text Documents Use an array containing multiple text documents. Each element represents a separate text document. { "text": [ "Text document 1", "Text document 2", ... ] }
- Input MIME type
- application/json
https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/en.map_entity.rxnorm_resolver.pipe/inputs/real-time
https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/en.map_entity.rxnorm_resolver.pipe/inputs/batch
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
text | Provide a single text document as a string. | Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out to support@johnsnowlabs.com .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
This model extracts biomarkers, classifies their presence, and links related entities in clinical text
Tavily MCP is a lightweight server that enables AI assistants to perform real time web search, intelligent crawling, and structured data extraction through the Model Context Protocol (MCP).
Tungsten Replicator for MySQL Sources is a replication engine that provides high-performance and improved replication functionality from MySQL, MariaDB & Percona Server, including Amazon RDS MySQL & Amazon Aurora.
In today's digital era, compliance with corporate transaction data is becoming increasingly important. Especially in the financial services industry, the security, legality and reliability of data are of paramount importance to enterprises. It covers a wide range of aspects, including but not limited to risk management, internal control, anti-money laundering and compliance management.
With the advancement of digital transformation, enterprises have a wider range of multiple channels for customer service. Data platforms, data types, and data quantities are also increasing rapidly. According to the requirements of compliance, the interaction, storage, query, analysis and extraction of these data have become the IT construction direction that enterprises pay attention to.
Extract text, data, photos, and signatures from all types of documents!
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.