Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

Extract Social Determinants of Health Free trial
By:
Latest Version:
5.5.4
Extract socio-environmental health determinants
Product Overview
Identify socio-environmental health determinants like access to care, diet, employment, and housing from health records. Tailored for professionals and researchers, this pipeline extracts key factors influencing health in social, economic, and environmental contexts. Process up to 2.8 M chars per hour for real-time and up to 12 M chars per hour for batch mode.
Key Data
Version
Type
Model Package
Highlights
This model is designed to detect and label social determinants of health (SDOH) entities within text data. Social determinants of health are crucial factors that influence individuals’ health outcomes, encompassing various social, economic, and environmental element. The model has been trained using advanced machine learning techniques on a diverse range of text sources.
The model can accurately recognize and classify a wide range of SDOH entities, including but not limited to factors such as socioeconomic status, education level, housing conditions, access to healthcare services, employment status, cultural and ethnic background, neighborhood characteristics, and environmental factors. The model’s accuracy and precision have been carefully validated against expert-labeled data to ensure reliable and consistent results
Covered entities: Access_To_Care, Age, Alcohol, Childhood_Event, Community_Safety, Diet, Disability, Education, Employment, Environmental_Condition, Exercise, Family_Member, Financial_Status, Food_Insecurity, Gender, Geographic_Entity, Healthcare_Institution, Housing, Hyperlipidemia, Hypertension, Income, Insurance_Status, Language, Legal_Issues, Marital_Status, Mental_Health, Obesity, Other_Disease, Population_Group, Quality_Of_Life, Race_Ethnicity, Sexual_Activity, Sexual_Orientation, Smoking, Social_Exclusion, Spiritual_Beliefs, Substance_Use, Transportation, Violence_Or_Abuse, etc..
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$23.76/hr
running on ml.m4.xlarge
Model Batch Transform$47.52/hr
running on ml.m4.2xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$0.24/host/hr
running on ml.m4.xlarge
SageMaker Batch Transform$0.48/host/hr
running on ml.m4.2xlarge
About Free trial
Try this product for 15 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
---|---|---|
ml.m4.xlarge Vendor Recommended | $23.76 |
Usage Information
Model input and output details
Input
Summary
Array of Text Documents: { "text": [
"Text document 1", "Text document 2", ...
] }
Single Text Document:
{ "text": "Single text document" }
JSON Lines (JSONL) Format
{"text": "Text document 1"} {"text": "Text document 2"}
Input MIME type
application/json, application/jsonlinesSample input data
Output
Summary
The output is a json structure containing all healthcare-related entities, the assertion status to the extracted entities and the relations between the extracted entities. See the details of the output structure here
Output MIME type
application/json, application/jsonlinesSample output data
Sample notebook
Additional Resources
End User License Agreement
By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)
Support Information
Extract Social Determinants of Health
For any assistance, please reach out to support@johnsnowlabs.com.
AWS Infrastructure
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