A trustworthy AI federated learning platform based on data privacy and human rights
Federated Platform introduction
- Ensure data privacy protection and respect human rights
- Standardize data format through a common data model
- Multiple types of labeling tasks and truthing mechanisms to ensure data quality
- Flexible filtering criteria for patient cohort selection.
- Unlock Medical Insights with International Coding System and Visualization Tools
- Efficient Patient Group Selection and Powerful Analytics
- Simplified model training with built-in diverse ML and DL models
- Optimize AI model with cross-site data
- Rapid clinical trials compliant with TFDA
- Automated Generation of Clinical Reports for Speed and Accuracy
If you want to perform medical statistical analysis on a large-scale databases
Patient Cohort selection
Researchers select patient cohort on the platform's large-scale medical data using ICD-10 and ATC codes
Conduct statistical analysis by built-in methods
Researchers study the selected patient population using built-in analytical methods on the platform.
If you want use valuable data to train a disease diagnostic or prediction model
Government health department
The hospital has medical image data and can make use of the platform's labeling function to annotate and locate lesions.
Automated initial model training
Once medical image data has been labeled, Model Zoo/AutoML can assist in constructing the initial model
Federated Learning for Performance Enhancement
After the initial model has been established, federated learning can contribute to performance enhancement.
Model performance validation
When the model meets clinical standards and requires validation for its effectiveness, federated validation can verify its performance using data from other hospitals
Trustworthy Federated Turnkey Solution: An all-encompassing AI platform that meets the diverse needs of users, integrating data governance, AutoML, federated learning, federated validation, and federated analysis functionalities.
The federated platform employs data governance to comply with GDPR for data privacy protection and respect for human rights. We utilize big data analysis to enhance clinical decision-making and patient management, and conduct cross-site model training and validation to provide more accurate predictions, increasing the possibility of patients' recovery.
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