Assess-AI utilizes a wide range of data from across your systems to analyze and report back detailed information on how your clinical AI is running at your institutions and give you comparisons to benchmarks. The data Assess-AI receives as input can be classified into four categories:
- Image study metadata.
- AI Results.
- Patient demographics.
- Radiology report text.
This data allows the Assess-AI registry to produce rich, high-fidelity analysis and information to guide your organization on the performance of your AI solutions.
These categories of data can be obtained from a variety of your local systems, including:
- PACS.
- VNA.
- AI Platform.
- AI Product.
- EHR.
- RIS.
- Data Warehouse/Lake.
Assess-AI, through ACR Connect, can integrate with these systems through a variety of protocols such as:
- FHIR.
- HL7v2.
- DICOM.
- DICOMweb.
- CSV.
For in-depth details on the data collected and ways to collect it, please see the Assess-AI Data Dictionary and Assess-AI Data Ingestion Guide.
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