Insights into FAIR and Analyzable Data
Quality-controlled biomedical data, analyzed by AI/ML, holds the key to unlocking new treatments and cures.
It starts with the data.
FAIRLYZ Blog: Data Sharing in the Era of AI
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Part 1: Data Providers at the NIAID Data Ecosystem Discovery Portal
The NIAID Data Ecosystem Discovery Portal allows exploring Infectious and Immune-mediated Disease (IID) data across many repositories through Resource Catalogs (collections of scientific information or research outputs) and Dataset Repositories (collections of data of a particular experimental type) that are…
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Earlier Detection, Better Outcomes with FAIR Data
Improving Early Disease Detection: FAIR data is being used to develop AI-powered tools that can analyze medical scans and detect diseases like Alzheimer’s or diabetic retinopathy at earlier stages, leading to better treatment outcomes. National Institutes of Health (NIH) –…
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Beyond the Hype: Why FAIR Data Matters for Real-World Medical AI Applications
The field of medical AI is buzzing with potential. From diagnosing diseases with superhuman accuracy to designing personalized treatment plans, AI promises to revolutionize healthcare. However, amidst the excitement, there’s a crucial element often overlooked: FAIR data. FAIR stands for…
FAIRLYZ Registry
Our comprehensive data sharing registry caters to a diverse group of researchers, ranging from investigators doing laboratory experiments to physician researchers and CROs running clinical trials.
FAIRLYZ Registry & Data QC
- Collaborate with fellow researchers
- Showcase your quality-controlled studies and data.
- Get funding for studies that reuse your data
- Run quality-control on your data or collaborators’ data

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