Explore freely available use cases focusing on critical content for algorithm development, including the value proposition, common data elements, and output parameters including radiologist decision support tools. Our use cases help radiologists and allied professionals by ensuring that AI tools provide needed information, can be efficiently implemented into daily workflow, and have the potential to improve patient care.
Services
We’re working with a variety of stakeholders — including the developer community — to inform development of clinically relevant AI that will benefit radiology and improve health care.
Define-AI
Certify-AI
Streamline the process for independently evaluating an algorithm’s performance ahead of the FDA pre-market review process by using our sequestered, multi-institution, well-qualified datasets. Services can be used individually or bundled together to determine if an algorithm performs well across imaging devices, clinical facilities and demographic populations.
Assess-AI
Capture real-world data during clinical use in a clinical data registry. Our service reports longitudinal algorithm performance data for use with algorithm improvement and meeting FDA post-market surveillance requirements. Performance reports are available for both developers and clinical sites.
ACR Assist
Modernize your reporting and unlock the value of your data with guidance for optimal radiologist interpretation of clinical scenarios, encoded into machine-readable modules. Each ACR Assistant includes information on required inputs of each clinical guidance scenario, as well as the logic to guide radiologists’ reports and recommendations.
FDA-Cleared Algorithm Catalog
Accelerate the process of vetting commercially available AI models with our easily searchable free catalog. Convenient summaries for each algorithm include model manufacturer, FDA product code, body area, modality, predicate devices, product testing and evaluation related to product performance, and clinical validation.
ACR Common
Simplify making one-to-one comparisons with this common language used across all ACR products and services. ACR Common is beneficial for organizations because it is based on a collection of common radiology terms and semantic structures, and organized around fundamental and derived axes such as scenario, procedure and finding.
Dataset Directory
Our list of datasets connects machine learning practitioners with accessible and meaningful datasets for their projects. The list includes organizations to contact about their datasets and organizations with datasets ready to be pulled directly from their websites.
Image Anonymization and Data Labeling
Protecting personal health information and preparing data appropriately for training and testing an algorithm can be difficult and time-consuming, but it is an area in which the ACR has developed significant experience through its clinical trials networks. We offer image anonymization and annotation tools and services to developers so they in turn can work with radiologists in a wide array of clinical settings to prepare images for use in AI development.