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.

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Closed-loop communication tool improves value of radiologists' recommendations

Patients might sometimes undergo unnecessary and costly evaluations when specialists do not provide referrers with all of the necessary information. 

ChatGPT chatbot

ChatGPT effectively simplifies radiology reports, presents 'real opportunity' to better inform patients

Radiology reports are typically written in language well above the average American adult’s eighth grade reading level, making them a source of confusion for patients.

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‘AI doctor’ reads radiology reports, other physician notes to predict patient outcomes

"Large language models make the development of ‘smart hospitals’ not only a possibility, but a reality,” said Eric Oermann, MD, an assistant professor in NYU's Department of Radiology. 

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Radiology practice suffers ‘significant’ cyberattack

Medford Radiology was left unable to see or report on images and was still assessing the scope of the attack as of May 30. 

Signify Research analyst Amy Thompson discusses connecting pathology and others with enterprise imaging systems.

Interest rising to connect pathology, other departments to enterprise imaging systems

Signify Research senior analyst Amy Thompson explains the trend of connecting various departments to enterprise imaging systems. She said digital pathology may soon become the third largest user of these systems.

artificial intelligence in radiology medical imaging interpretation

Interpretive AI for medical imaging: 5 points of skepticism, idealism

Surveying the landscape of interpretive AI in radiology, two researchers note a yawning gap between great expectations set in the recent past and actual clinical implementations as of spring 2023.

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New AI tool helps radiologists reduce read times by up to 40%

Its use dropped the average time needed to examine a finding at all timepoints from 107 seconds to 65 seconds, with pulmonary nodule assessments benefiting from the greatest reductions.

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Remote radiologists prioritize financial gain when choosing reads: 2 possible fixes

An intense focus on RVU productivity may have unintended negative consequences, experts wrote in the Journal of Operations Management.