Deep Learning-Based Medical Research Platform

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What you can do with m:Studio?

Preliminary Result

With smart augmentation, similar performance can be achieved with a fraction of normal training data and making it easier to get preliminary result.

AI Model Creation & Test

m:Studio provides a user-friendly interface for labeling and an intuitive model training environment that requires little supervision allowing faster model creation and accurate inference.

Research Achievement

With less focus on getting large amount of labeled data, training and model tuning, research can be prioritized.

Exclusively offered by m:Studio

Easy and
Semi-Automatic Annotation

Minimize the hassle.
Simple touch for swift traning.

Smart Data Augmentation

Populated data for training and validation. AI presents the consistent and many results.
Platform functions made for realizing your ingenuity through AI.

Seed Training Models

m:Studio AI model set that were trained using 6,000 stroke cases and more than 140,000 CT images.
It makes your seed training Deep Learning models.
m:Studio differentiates Deep Learning from the frustration.

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How does m:Studio work?

Pricing Information

We offer the most economical package for medical AI model development.

Data Size (Number of DICOM files) Price ($)
1,001 ~ 5,000 $1,500
5,001 ~ 10,000 $2,000
10,001 ~ 50,000 $3,000
50,001 ~ 100,000 $5,000
100,001 Over Negotiable
Start your m:StudioBrochure

Walk with
CAIDE Systems

Let Us Know Your Specific Research Focus.

Any Body Part and Any Disease

CAIDE Systems Offers Deep Learning Training Assistance.

Development of your own AI Model(s).

Ultimate Goal is Platform Community.

Distribute Disease Detection AI Models: A Market Portfolio

https://www.youtube.com/watch?v=auwCwAoShr8

m:Studio is a packaged platform that allows users to operate multiple medical Deep Learning research projects.
The platform is designed to support you for the detection of diseases and symptoms on body parts and organs.
Deep Learning based algorithms can be developed with platform and for academic findings.