Federated learning (FL) is a machine learning method that enables multiple parties to collaboratively train a model orchestrated by a trustable central server while keeping data locally. Taiwan AI Labs built up the first open-source federated learning framework (FL framework) in Taiwan. AILabs FL framework is widely deployed and used across medical centers and regional hospitals in Taiwan. It obtains huge reputation due to its privacy protection mechanism, cross-institutional collaboration, including model training (Federated Learning, FL), validation (Federated Validation, FV®).
Comprehensive Data Governance Support
Holistic data governance tools including curation, quality control, preprocessing and labeling. Providing unified normalization approaches to standardize data excellence and usage.
Human-Centered Privacy Compliance
Privacy protection first – complying with GDPR by data deidentification, anonymization , pseudonymization with user consent.
Simultaneous multiple-site, multiple-project training processes, with managing dashboard to create, join projects, to upload AI model but keep datasets locally, and to setup with flexible schedule and fault-tolerant network. Advanced aggregation algorithms for better performance and best local model output.
Cross-site, cross-vendor federated validation mechanism provides an easy solution to validate AI model to avoid data bias and discrimination.
Taiwan AI Federated Learning Alliance (https://taifa.org/) assembles more than 90 members from medical and other industries, government, and academy. They form Federated Learning Alliances in areas such as medical, financial, transportation, manufacturing, etc., to advocate and implement Federated Learning in order to solve data silo issues.
TFDA Integrated Service
Cooperate with the Taiwan Clinical Trial Consortium (TCTC) for field validation while customizable tools are provided for CRF/CSR reports during CDE/TFDA/FDA SaMD clinical evaluation progress.
Production Traceability and Certification
ISO/IEC 27000, ISO/IEC 29000 and CNS 29100 privacy compliance. OWASP (open web security project) SAST (static application security testing) and DAST (dynamic application security testing) ensure.
Medical System Integration
A complete set of API connectors to link hospital HIS/PACS/RIS/FHIR/OHDSI/CDISC/MIMIC-IV/… systems. Effortless deployment to streamline data flow.
Privacy protection is the most important thing. With Taiwan AI Labs Federated Learning mechanism, we can keep data in the original places while doing AI model training at the same time. Click here to understand how Taiwan AI Labs FL Framework works to protect user privacy.
Taiwan AI Labs proposes the first-ever Federated Validation (FV®) solution to the world and demonstrate how it works among several prestigious national medical centers in Taiwan. To understand more about Federated Validation, please Click here.
A world-class, human-oriented precision medical system constructed in Taiwan
TAIMedImg combines the cutting-edge image recognition technology developed by Taiwan AI Labs with the extraordinary clinical teams, learns to identify lesions from experienced professionals, speeds up the interpretation of medical images, improves the quality of medicine, and creates a world-class ” AI-assisted medical center”.