Leveraging generative AI to accelerate public health genomics data standardization | Amazon Web Services
Transforming fragmented public health data into standardized formats is a growing challenge. This blog post from AWS illustrates how generative AI is helping accelerate that process, particularly for genomics data used in public health. Read the blog for insights on how AI is improving data access and streamlining analysis, and reach out to Advanced Innovative IT Solutions LLC to explore AI strategies for your agency's evolving data needs.
What is the AI Genomic Schema Harmonizer?
The AI Genomic Schema Harmonizer is a generative AI-powered application designed to help laboratories prepare genomic data for submission to public repositories. It streamlines the standardization process by automatically aligning diverse laboratory terminologies with standardized formats, significantly reducing the time and effort required for data preparation.
How much time can laboratories save using this application?
Laboratories can save approximately 2 to 4 hours per week per data submission by using the AI Genomic Schema Harmonizer. This translates to over 400 hours annually per laboratory that can be redirected towards critical analysis and response activities.
What are the implications for data accuracy?
The application enhances data accuracy by eliminating typographical errors that often occur during manual data preparation. By automating the alignment of terms with standardized definitions, it reduces the risk of submission rejections or corrections, thereby facilitating quicker and more compliant submissions.
Leveraging generative AI to accelerate public health genomics data standardization | Amazon Web Services
published by Advanced Innovative IT Solutions LLC
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From ransomware prevention and compliance audits to cloud migrations and 24/7 system monitoring, our team delivers enterprise-level solutions with a personal, customer-first approach. At AIIS, we believe technology should be a tool that drives success—not a hurdle.
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