2023 Imaging Informatics Preview

Road to RSNA 2023: Imaging Informatics Preview

In many respects, AI has come to dominate the field of imaging informatics research, a trend that will be evident at RSNA 2023.

November 17, 2023

AI reduced CT brain reporting time in teleradiology

An AI algorithm deployed to assist with noncontrast CT brain reports in Australia cut radiologist reporting time by up to 8.5%, according to this scientific session.

November 16, 2023

Seeking trustworthy automated detection for hip implant

A deep-learning classifier designed to create a deep-learning “trustworthiness pipeline,” in this case for a total hip arthroplasty aid in clinical settings, recognized 28 implants on plain hip radiographs, according to recent research.

November 16, 2023

Locally derived calibration sets prove useful for predicting AI performance

In this presentation, researchers will reveal how they were able to improve AI algorithm performance by utilizing local data.

November 16, 2023

Novel method aims to stop white-box, black-box attacks on AI diagnosis models

Citing vulnerabilities with deep learning-based mammographic breast cancer diagnosis models, a University of Pittsburgh research team has developed and evaluated a novel technical framework that could defend against adversarial attacks on AI software.

November 16, 2023

Are LLMs effective without specific training?

Researchers seeking to speed up the development of large-language models (LLMs) are exploring where and how to use a training technique called zero shot, as this Wednesday session will cover.

November 16, 2023

ChatGPT-4 delivers differential diagnosis on abdominal imaging

This Tuesday afternoon session will show how ChatGPT-4 performed for producing a differential diagnosis from transcribed radiology reports of abdominal imaging exams.

November 16, 2023

NLP tool helps make radiology reports more readable

Researchers from the Yale School of Medicine have developed a patient-centric radiology literacy tool using natural language processing (NLP) technology and prompt engineering to produce radiology reports that are more readable for patients.

November 16, 2023

AI model shows promise for spotting errors in CXR reports

A deep-learning algorithm may be able to help reduce diagnostic errors in radiology, according to this presentation on Monday morning.

November 16, 2023

NLP technique eases reporting requirements

Using natural language processing (NLP) for real-world evidence gleaned from radiology reports could relieve burdens on those with reporting requirements related to postmarket safety of cancer drugs, according to a Monday morning presentation.

November 16, 2023

Macro tool tracks incidental findings for follow-up

When a large academic health system used standardized consensus-based macros to track actionable incidental findings most found the macros helpful because they saved time and ensured appropriate follow-up, according to a project to be presented Monday.

November 16, 2023

Machine-learning model prioritizes STAT imaging orders

If you have considered that a “STAT” designation on imaging orders could be overutilized, misused, or obscure the urgency of the order, you will want to hear how an automated system has been designed to prioritize some STAT orders to the top of the queue.

November 16, 2023

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