Algorithms

This page describes a feature of Haut.AI SaaS Platform that allows you to perform AI analysis of image data.

Algorithms feature is available for all plans, but some Algorithms are included only in Professional plan

Algorithms section is available as App Marketplace section in SaaS

About Algorithms

Algorithms is an AI core functionality of Haut.AI products. Algorithms enable AI image analysis. Algorithms can be used:

Algorithms are organized into Applications, that combine one or more algorithms.

There are several Applications available for usage in all plans:

  • Face Metrics 2.0 Application, check more here: Face Metrics 2.0 Application

  • Hair Metrics 2.0 Application

  • Recommendation Engine Application

  • Beautification Application

There are several Applications available for usage only in the Professional plan:

  • Acne Pro Application

  • Pigmentation Pro Application


Getting Started with Algorithms

To be calculated, Algorithms require a Dataset with images to be created first.

To create a new Dataset, follow the guide Getting Started with Datasets

  1. Open an Algorithms Application by clicking on the name of the application.

  2. Click the “Attach application” button.

  3. Choose an existing Dataset in the drop-down menu "Choose dataset to run this application."

  4. Click "Start."

Now the selected Algorithms Application is attached to the Dataset and all the images, that will be uploaded to this Dataset afterwards will be processed with all the Algorithms in this Application.

Algorithms Applications do not have historical data processing!

It means that all images, uploaded to the Dataset BEFORE attaching the Algorithms Application will not be processed with this Application.


FAQ

What is the cultural diversity profile of the algorithms in the Skin SaaS platform?

Our algorithms are agnostic to phenotype and skin tone. We use diverse and balanced datasets and best practices in diverse AI to train our models.

How were the algorithms validated?

Our algorithms are validated against clinical evaluation criteria. The quality analysis of the algorithms and the data annotation are implemented by data scientists, dermatologists, biologists, and skin experts. The algorithms are not certified as medical devices, but the methods were described in publications in peer-reviewed journals. Check out the Haut.AI articles here.

Example: Eye Are Condition Algorithm from Face Metrics 2.0 Application includes three submetrics: Dark Circles Score, Eye Bags Score, and Lacrimal Grooves Score.

Example: Pores Algorithm from Face Metrics 2.0 Application includes Masks showing detected pores poisition on face.

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