Leveraging Clinical Data Treasures: Integration of an AI Platform into Clinical IT

Area of Science:

• Clinical Informatics
• Artificial Intelligence in Medicine
• Health IT Integration

Background:

• Rapid expansion of artificial intelligence (AI) in clinical settings necessitates structured frameworks.
• Existing systems often lack integrated solutions for the complete lifecycle of clinical AI models.
• Need for seamless integration of AI tools within current healthcare IT infrastructure.

Purpose of the Study:

• To introduce a novel clinical AI platform designed to support the entire development cycle of AI models.
• To ensure the practical application and management of clinical AI models within healthcare environments.
• To demonstrate the integration of the clinical AI platform with existing clinical IT systems, including data integration centers.

Main Methods:

• Development of a comprehensive clinical AI platform.
• Focus on integrating the platform with clinical IT infrastructure.
• Inclusion of medical data integration centers in the platform's design.
• Evaluation through a specific clinical AI use case.

Main Results:

• The proposed platform facilitates the end-to-end management of clinical AI models.
• Successful integration with clinical IT infrastructure, including data integration centers, was demonstrated.
• The use case validated the platform's functionality and applicability in a real-world clinical scenario.

Conclusions:

• The developed clinical AI platform effectively supports the development, management, and application of AI models.
• Integration with clinical IT is crucial for the successful adoption of AI in healthcare.
• The proposed framework offers a scalable solution for advancing AI in the clinical domain.