CDSS (Clinical Decision Support System) is one of the objectives of the ari, the purpose is to demonstrate how to develop AI and turn it into practical SaaS (software as a service) application software.

During the development of AI model, CDSS provides data analysis and statistics. When the data is imbalanced, AI learning will be inaccurate. Therefore, the data sorting in advance will greatly affect the final result. The ready-made AI model must be improved through a large number of test data to be perfect. Through CDSS, you will be able to understand the maturity of the model and the areas that need to be improved without looking at the code. The visual analysis tools and intuitive interactive interface allow you to more easily decide whether to completely hand over the model improvement process to the built-in automl system, or modify the algorithm to produce AI models that meet your own needs. In short, ari's CDSS is a diagnostic auxiliary function that integrates AI model training, data analysis, and even directly uses the developed AI analysis model to determine the positive and negative of the disease, as well as the estimation of the incidence rate.


Accelerate medical education and training


Reduce doctor workload and patient waiting time


Provide accurate and real-time information to assist doctors in decision making


Comprehensive treatment and clinical guidelines to ensure the safety and quality of patient care


The modified and trained AI model can be deployed directly


Improve reliability with interpretable models, making AI no longer a black box


Collaboration with data scientists, combined with Know-How for terminal application requirements


Intuitive graphical user interface, simplifying complexity




Model Training

Loading the existing AI model directly makes it easy to retrain

Data Analysis

Use multiple indicators to comprehensively evaluate the pros and cons of AI models and verify their credibility

Online Inference

Provide AI model evaluation tools and graphical data analysis tools

Auto Labeling

Accelerate the development of machine learning model for image recognition and shorten the training time

DICOM Viewer

Designed for 3D medical image viewer, supports [3D image viewing] [DICOM format conversion] [labeling tool]


Data/model analysis tools and simple inference interface

案例應用 Applications

隨著 AI 越來越強大,高效的 AI 平台或開發環境也成為每個行業的重要需求。


As AI becomes more and more powerful, an efficient AI platform or development environment has become an important demand of every industry.

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