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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.

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Medical Speech to Text Free trial

Latest Version:
5.2.9
Transform medical voice recording to text and extract entities

    Product Overview

    The Medical Speech to Text Model converts spoken language into written text, specifically tailored for the medical field. The resulting text is further analyzed and relevant medical entities are extracted together with assertion statuses for those and relations between them.

    Key Data

    Highlights

    • Key Features

      • Medical Voice Recognition: Utilizes state-of-the-art voice recognition technology that is finely tuned to the nuances of medical terminology and diverse accents found in the medical environment.

      • Entity Recognition: Beyond simple transcription, this model is equipped with sophisticated Natural Language Processing (NLP) capabilities. It automatically identifies and categorizes key medical entities such as symptoms, diagnoses, medications, and dosages within the transcribed text.

    • Detected entities: Admission_Discharge, Age, Alcohol, Allergen, BMI, Birth_Entity, Blood_Pressure, Cerebrovascular_Disease, Date, Diabetes, Diet, Direction, Disease_Syndrome_Disorder, Dosage, Drug_BrandName, Drug_Ingredient, Duration, EKG_Findings, Employment, Form, Frequency, Gender, HDL, Heart_Disease, Height, Hyperlipidemia, Hypertension, ImagingFindings, Imaging_Technique, Procedure, Pulse, Race_Ethnicity, Relationship_Status, RelativeDate, RelativeTime, Respiration, Route, Smoking, Strength, Substance, Symptom, Test, Test_Result, Time, Treatment,etc.

    • Assertion status: Each identified entity is qualified as Hypothetical, Someoneelse, Past, Absent, Family, Planned, Possible or Present. Relations: The model detects three relations: is_finding_of, is_date_of, is_result_of

    Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us

    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$95.04/hr

    running on ml.m4.4xlarge

    Model Batch Transform$95.04/hr

    running on ml.m4.4xlarge

    Infrastructure 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$0.96/host/hr

    running on ml.m4.4xlarge

    SageMaker Batch Transform$0.96/host/hr

    running on ml.m4.4xlarge

    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.m4.4xlarge
    Vendor Recommended
    $95.04
    ml.c5.9xlarge
    $213.84
    ml.c5.4xlarge
    $95.04
    ml.m4.2xlarge
    $47.52

    Usage Information

    Model input and output details

    Input

    Summary

    Supported audio file formats include: mp3, wav, aac, m4a.

    Limitations for input type
    11MB
    Input MIME type
    application/octet-stream
    Sample input data

    Output

    Summary

    The output consists of a JSON object with the following structure:

    { "document": "Transcribed text of the document", "segments": [ { ... }, ... ], "ner_predictions": [ { ... }, ... ], "assertion_predictions": [ { ... }, ... ], "relation_predictions": [ { ... }, ... ] }

    Output MIME type
    application/json
    Sample output data

    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

    Medical Speech to Text

    For any assistance, please reach out to support@johnsnowlabs.com.

    AWS Infrastructure

    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.

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    Refund Policy

    No refunds are possible.

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