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.

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70-year-old radiology practice suffers cyberattack

Cheyenne Radiology Group said the incident may have resulted in the inadvertent exposure of patients’ personal information. 

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AI boosts value of CT lung cancer screening by helping predict death from other diseases

Experts see great promise for improving population health outcomes with such opportunistic screening via low-dose CT, according to a study published in Radiology

#CTA #acuteischemicstroke #AIS #radiomics

Evidence supporting use of radiomics is 'insufficient' and 'weak,' according to new meta-analysis

Although the predictive power of radiomics has been touted as a tool that could improve patient outcomes, the method has a long way to go before it can be reliably introduced into real-world clinical environments.

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Many physicians are unaware that interventional radiology is a distinct specialty

This could pose as a barrier to referrals for image-guided interventions for radiologists specializing in IR, authors of a new paper in Clinical Imaging suggested.

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ImpressionGPT, a ChatGPT-based framework, can accurately summarize radiology reports

The program leverages the in-context learning abilities of large language models to generate report summaries using domain-specific, individualized data relative to radiology.

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Natural language processing can limit report discrepancies between AI and radiologists

Journal of the American College of Radiology study details how one radiology department  implemented NLP software to resolve inadvertent discordance between physicians and an AI decision support system.

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The good and the bad of synoptic radiology reports

Synoptic radiology reports with detailed information on disease sites in ovarian cancer could help to guide surgical decisions, but they can come at a cost.

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ChatGPT excels at radiology referrals in emergency departments

With proper training, large language models could help address inappropriate imaging referrals, which are common in EDs, experts write in the Journal of the American College of Radiology.