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Features Glass Health
Large Language Model
Experts at Glass use the foundational large language model which helps generating differential diagnosis or clinical plans based on clinical problems representation.
Clinical Knowledge Database
A comprehensive database maintained by clinicians, seamlessly integrated with AI to support in generating diagnosis or draft clinical plan.
De-Identification of Data
The platform ensures that no protected health information about patients is entered, prioritizing user privacy and data safety.
Contextual Information Integration
It uses context like evidence-based guidelines, schemas, and case studies for high-level clinical excellence in AI outputs.
Qualified AI Outputs
All AI outputs are made to be interpreted carefully and not replace or serve as substitute for professional judgment of healthcare provider.
No Medical Image Input
The application is not designed to process or analyze a medical image, signal from an in vitro device or signal acquisition system.
Adjustable Output Quality
Quality of the AI output is dependent on input quality, making it flexible to provide best possible results.
Feedback Enhancement
Users' feedback is utilized for the constant development of the Glass AI, making it more accurate and user-friendly over time.