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.

AI detects twice as many incidental lesions as radiologists
Prior research has suggested that these incidental lesions turn out to be cancerous in up to 70% of cases, making their timely detection critical.
New teleradiology solution promises to streamline enterprise imaging operations
Konica Minolta and NewVue announced their collaboration on cloud-based Exa Teleradiology earlier this week.
Fine-tuned LLMs show great promise for spotting radiology report errors
Report errors can result in incorrect or delayed diagnoses and significantly impact disease management.
Predictive model cuts back on unnecessary imaging requests for headaches in the ED
Headaches are a common complaint among patients presenting to the emergency department, with millions of cases documented annually in the United States.
First-of-its-kind framework monitors real-time performance of radiology AI tools
The program provides detailed assessments of how algorithms implemented into workflows are impacting efficiency and outcomes.

Konica Minolta Healthcare Americas Inc. and ImagineSoftware announced an integration agreement to integrate the ImagineOne artificial intelligence (AI)-driven platform for automated radiology billing with Konica Minolta’s Exa PACS-RIS solution.

Konica Minolta and ImagineSoftware partner to expand revenue cycle management offerings

Konica Minolta partnered with ImagineSoftware to integrate its AI-driven revenue cycle management platform into the Exa PACS-RIS solution.

Chinese hackers use malware disguised as imaging viewers to steal patient data

The software has been primarily disguised as Philips’ DICOM MediaViewerLauncher.exe—a trusted program that enables patients to view their medical imaging on their own personal servers.

Jason Poff, MD, director of innovation deployment for artificial intelligence (AI) at RadPartners, explains the five-step process he uses to evaluate medical imaging AI.

5 steps for evaluating radiology AI applications

Jason Poff, MD, director of innovation deployment for artificial intelligence at Radiology Partners, explains the process he uses to evaluate medical imaging AI.

AI detects subtle changes in images over time.

Adaptable AI system detects subtle changes in imaging, has potential across multiple clinical settings

The Learning-based Inference of Longitudinal imAge Changes, or LILAC, system harnesses machine learning to review medical images that have been collected over a prolonged period.

PocketHealth's Image Readers helps patients understand their radiology report findings.

Newly launched report feature provides patients with a visual aid to their imaging

The artificial intelligence-enabled feature can be integrated directly into patients’ imaging results.

New algorithm models radiologists' eye movements to interpret chest X-rays

The algorithm has an edge over standard black box-style artificial intelligence applications because providers are able to see how it reaches conclusions.

How radiology groups can contain damage from future cyberattacks

Radiologists with Harvard Medical School gave guidance to peers in a perspective piece published Tuesday in Academic Radiology.

Risk prediction algorithm slashes number of unnecessary thyroid nodule biopsies

Although the vast majority of nodules are benign, many are referred for biopsy as a precaution to rule out malignancy.

Imaging Informatics

AI detects twice as many incidental lesions as radiologists

New teleradiology solution promises to streamline enterprise imaging operations

Fine-tuned LLMs show great promise for spotting radiology report errors

Predictive model cuts back on unnecessary imaging requests for headaches in the ED

First-of-its-kind framework monitors real-time performance of radiology AI tools