Imaging Informatics

Imaging informatics (also known as radiology informatics, a component of wider medical or healthcare informatics) includes systems to transfer images and radiology data between radiologists, referring physicians, patients and the entire enterprise. This includes picture archiving and communication systems (PACS), wider enterprise image systems, radiology information. systems (RIS), connections to share data with the electronic medical record (EMR), and software to enable advanced visualization, reporting, artificial intelligence (AI) applications, analytics, exam ordering, clinical decision support, dictation, and remote image sharing and viewing systems.

Prompts matter: How input elements affect large language model performance
Just like radiologists, the performance of large language models improves when given proper context.
AI can help radiology standardize image exam data labeling
To fully leverage today's radiology IT systems, standardization is a necessity. Steve Rankin, chief strategy officer for Enlitic, explains how artificial intelligence can help.
ACR partners to create AI foundational model assessment website
Christoph Wald, MD, vice chair of the American College of Radiology Board of Chancellors, explains the partnerships with academic institutions to create the Health AI Challenge will help provide a better understanding of how foundational AI models work.
Commercially available AI increases breast cancer detection by nearly 20%
Results from the world’s largest prospective artificial intelligence study revealed the system could significantly benefit breast cancer screening programs.
ACR Assess-AI national data registry tracks performance of clinical algorithms
Christoph Wald, MD, vice chair of the ACR Board of Chancellors, explains how the new Assess-AI National Radiology Data Registry is designed to help monitor accuracy and other metrics for radiology artificial intelligence.

Optimizing Coronary CTA Workflow: How We Do It

Coronary CT angiography (CCTA) provides an accurate evaluation of coronary-artery disease and coronary-artery anomalies, and it gives us the ability to evaluate the cardiac chambers, myocardium, and valves. Effective deployment of CCTA service requires optimization of workflow to make this procedure cost effective and practical.

Imaging Informatics

Prompts matter: How input elements affect large language model performance

AI can help radiology standardize image exam data labeling

ACR partners to create AI foundational model assessment website

Commercially available AI increases breast cancer detection by nearly 20%

ACR Assess-AI national data registry tracks performance of clinical algorithms