Sold by: ElectrifAi LLCÂ
Deployed on AWS
Free Trial
To help identify skin mutations to support clinical decisions and diagnosis.
Overview
To help identify skin mutations to support clinical decisions and diagnosis. Non-melanoma skin cancers, such as Basal Cell Carcinomas (BCC) and Squamous Cell Carcinomas (SCC), are the most common human skin cancers and they are growing fast. By inputting an image (.jpg, .png, or .bmp), the model outputs a probability value between 0 - 1 indicating the likelihood of BCC or SCC skin cancer. The model does not do disease detection or symptom extraction. To preview our machine learning models, please Continue to Subscribe. To preview our sample Output Data, you will be prompted to add suggested Input Data. Sample Data is representative of the Output Data but does not actually consider the Input Data. Our machine learning models return actual Output Data and are available through a private offer. Please contact info@electrifai.net for subscription service pricing. SKU: SKINC-PS-HLC-AWS-001
Highlights
- To help identify skin mutations to support clinical decisions and assist in diagnosis of skin cancers such as Basal Cell Carcinomas and Squamous Cell Carcinomas.
- The following model has not been FDA cleared and/or approved and must be used under guidance or supervision of an institutional review board. The model must be used by an appropriately trained or licensed healthcare provider and shall not be solely or primarily relied upon to diagnose, treat, prevent, cure, triage, monitor, investigate, predict outcome and/or used as a response to treatment for patients who have a specific skin disease. The recommendations provided by the product are adjunctive to any additional information gathered by a professional.
- Use of this model should be in line with local and state regulations. This model is not indicated for the diagnosis of specific skin disease(s), but merely provides interpretation of the images.
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Free trial
Try this product free for 14 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.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $700.00 |
ml.p2.16xlarge Inference (Real-Time) Recommended | Model inference on the ml.p2.16xlarge instance type, real-time mode | $700.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $900.00 |
ml.m5.large Inference (Batch) | Model inference on the ml.m5.large instance type, batch mode | $500.00 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $500.00 |
ml.p3.16xlarge Inference (Real-Time) | Model inference on the ml.p3.16xlarge instance type, real-time mode | $900.00 |
Vendor refund policy
No Refunds.
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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
Vulnerability CVE-2021-3177 (i.e. https://nvd.nist.gov/vuln/detail/CVE-2021-3177 ) has been resolved in version 1.0.1.
Additional details
Inputs
- Summary
Input: 1 image in .jpg, .bmp or .png format
- Input MIME type
- application/json
https://github.com/ElectrifAi/model-aws-skin-marking-classification-model/blob/main/input.jpg
https://github.com/ElectrifAi/model-aws-skin-marking-classification-model/blob/main/input.jpg
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
.jpg | Input: 1 image in .jpg, .bmp or .png format | Type: FreeText | Yes |
.bmp or .png format | Input: 1 image in .jpg, .bmp or .png format | Type: FreeText | Yes |
Resources
Vendor resources
Support
AWS infrastructure support
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