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.

RamSoft and Alpha Nodus partner to streamline imaging prior authorization processes
RamSoft, a leader in cloud-based RIS/PACS radiology solutions, and Alpha Nodus, a developer of AI-driven administrative tools for medical offices, announced their partnership on Wednesday.
MRI-based Node-RADS effectively improves staging of head and neck cancer
Use of the scoring system could offer providers valuable preoperative insight and help guide them in surgical decisions.
What radiologists think about using ChatGPT and AI in breast imaging
Manisha Bahl, MD, explained that ChatGPT and other large language models offer significant potential to help radiologists with breast imaging exams, but they are "not quite ready for primetime."
AI beats standard regression models at predicting lung cancer risk
Not all AI or regression models are the same, nor do they all incorporate the same data when assessing patient risk.
Newly proposed cybersecurity rule could cripple private radiology practices, RBMA says
This marks the first major update to the HIPAA Security Rule in over a decade, with HHS seeking to require multifactor authentication and written documentation of all policies.

Many radiology PowerPoints inadvertently put private health information at risk

Many of these files are still readily available online, and numerous contain PHI that is “easily accessible,” a new analysis reveals.

Incidental finding characteristics that warrant communication

Three factors are associated with true high-risk findings—imaging protocols for aortic valve implantation planning, imaging area, and cardiology department orders.

GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports

The large language model can also outperform other human providers, radiologists included, new study shows.

Providing chatbots with guideline context significantly improves their imaging recs

With proper prompts and appropriate context, chatbots can play a valuable role in imaging referrals.

Referring providers share preferences for radiology report templates

New research suggests that there might not be a straightforward answer to questions related to which type of reporting method is ideal.

Large language models not quite ready for cancer staging responsibilities

Although LLMs have seen rapid advancement in recent years, they still cannot compare to human radiologists when it comes to staging cancer using free text reports.

radiology report bubbles translate informatics imaging

Automated feedback improves trainee reports, especially during after-hours

Such tools can be especially beneficial for trainees working late-night shifts, when quality feedback is generally delayed and more difficult to come by.

Many radiologists still unfamiliar with opportunistic screening applications

Although AI implementation in clinical practice has taken flight in recent years, opportunistic screening utilization has been less common.

Imaging Informatics

RamSoft and Alpha Nodus partner to streamline imaging prior authorization processes

MRI-based Node-RADS effectively improves staging of head and neck cancer

What radiologists think about using ChatGPT and AI in breast imaging

AI beats standard regression models at predicting lung cancer risk

Newly proposed cybersecurity rule could cripple private radiology practices, RBMA says