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 entities from mental-health data Free trial
By:
Latest Version:
5.5.4
Identify mental-health entities,assign assertion status and establish relations between the extracted entities
Product Overview
This model is specialized in analyzing and extracting mental-health entities such as opioid drugs, substance use, substance quantity,, symptom, drug information like dosage, duration, route, form, frequency,strength, etc, procedures, treatment and test , patient social information and more. This model is tailored for gleaning crucial insights , proficiently identifying entities like gender, age, substance abuse, psychological conditions, and many more. By leveraging this pipeline, medical professionals can gain a more comprehensive understanding of the patient experience, ensuring care that is both patient-centered and data-informed. Analyse up to 1.7 M chars per hour for real time processing and up to 5.5 M chars per hour for batch processing.
Key Data
Version
Type
Model Package
Highlights
Extracted Entities: Mental_Health, Opioid_Drug, Substance_Use, Substance_Quantity, Injury_or_Poisoning, Symptom, Drug, Drug_Dosage, Drug_Duration, Drug_Route, Drug_Form, Frequency, Drug_Strength, Procedure, Treatment, Test, Test_Result, Gender, Age, Disease_Syndrome_Disorder, Smoking, Alcohol, Social_Exclusion, Family_Member, Childhood_Event, Disability, Eating_Disorder, Violence_Or_Abuse
Assertion Status Labels: Present, Absent, Possible, Planned, Past, Family, Hypotetical, SomeoneElse
Relation Extraction Labels:
Drug,Drug_Dosage,Drug-Frequency,Drug-Duration,Drug-Drug_Strength, Test-Test_Result, Disease_Syndrome_Disorder-Symptom, Disease_Syndrome_Disorder-Drug, Symptom-Drug, Treatment_Drug, Symptom-Treatment, Disease_Syndrome_Disorder-Treatment, Treatment-Drug, Disease_Syndrome_Disorder-Procedure, Procedure-Drug, Mental_Health-Opioid_Drug, Mental_Health-Substance_Use, Mental_Health-Injury_or_Poisoning, Mental_Health-Symptom, Mental_Health-Drug, Mental_Health-Procedure, Mental_Health-Treatment, Mental_Health-Test, Mental_Health-Gender, Mental_Health-Age and much more.
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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
Input Format
- Single Text Document { "text": "Single text document" }
- Array of Text Documents
{
"text": [
] }"Text document 1", "Text document 2",
- 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 mental 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 entities from mental-health data
For any assistance, please reach out to support@johnsnowlabs.com.
AWS Infrastructure
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