Enterprise Imaging

Enterprise imaging brings together all imaging exams, patient data and reports from across a healthcare system into one location to aid efficiency and economy of scale for data storage. This enables immediate access to images and reports any clinical user of the electronic medical record (EMR) across a healthcare system, regardless of location. Enterprise imaging (EI) systems replace the former system of using a variety of disparate, siloed picture archiving and communication systems (PACS), radiology information systems (RIS), and a variety of separate, dedicated workstations and logins to view or post-process different imaging modalities. Often these siloed systems cannot interoperate and cannot easily be connected. Web-based EI systems are becoming the standard across most healthcare systems to incorporate not only radiology, but also cardiology (CVIS), pathology and dozens of other departments to centralize all patient data into one cloud-based data storage and data management system.

Enlitic

Radiology data sharing vendor Enlitic to acquire rival for $5M

The Fort Collins, Colorado, company is purchasing all shares of Laitek Inc., a major provider of medical imaging data migration and routing services in the U.S. 

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Why PACS should be part of undergrads' medical education

Many traditional radiology courses leave out hands-on opportunities for students—something that could greatly benefit their understanding of the specialty.

Example of AI automated detection and highlighting of critical lung findings on a chest X-ray for a possible lung cancer nodule and fibrosis. Example shown by AI vendor Lunit.

PHOTO GALLERY: Examples of FDA-cleared AI in radiology

This is a photo gallery of artificial intelligence products cleared for clinical use in medical imaging by the U.S. Food and Drug Administration. Radiology by far is the leader of all clinical AI FDA approvals.

nonclinical augmented intelligence american medical association

ChatGPT's medical writing is getting so good that it may soon fool AI detectors

The large language model’s medical manuscripts are becoming so well constructed that it can be difficult to distinguish them from those compiled by humans. 

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Providers' opinions on giving patients open access to their radiology reports are evolving

Online access to medical records has become standard practice, making sharing radiology reports and communicating findings much more streamlined.

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AI rules out abnormal findings on chest X-rays, significantly reducing workloads

The commercially available software can correctly exclude pathology on chest radiographs with accuracy rates similar to those of radiologists.

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How GPT-4 can improve radiology resident report feedback

With resources stretched thin at many facilities, this type of feedback can often be limited.

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Radiology information systems provider reports data breach

The cyberattack impacted patient information including dates of birth, driver’s license and Social Security numbers, medical records, and health insurance details.