An advanced AI solution addressing critical challenges in retinal image analysis for healthcare. Current solutions lack precision, deliver limited insights, face scalability issues, and create inefficient workflows that hinder accurate diagnoses of conditions like diabetic retinopathy and glaucoma.
The proposed solution leverages AWS Bedrock, BioLAMA, and cloud architecture including S3 storage, Lambda functions, and DynamoDB to provide high-fidelity retinal image analysis.
Built with Streamlit for user-friendly interfaces and Python backend integration, the system achieves impressive outcomes: 85% improved diagnostic reliability, 90% scalable deployments, and 75% enhanced clinical workflows, significantly improving patient care and operational efficiency.
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