Erik L. Ridley is a journalist who writes for AuntMinnie.com and Cook Medical Australia. His articles primarily cover topics related to medical imaging and radiology, including updates from industry conferences, advancements in technology, and discussions on the use of artificial intelligence in healthcare.
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Erik L. Ridley's coverage focuses on scientific and tech themes within the healthcare sector, particularly in radiology and medical imaging. He regularly cites data, publishes press releases, and covers private sector announcements.
Given his focus on scientific and tech topics related to healthcare, Erik would likely be interested in receiving pitches from experts with deep knowledge of the latest advancements in radiology technology or those who can provide valuable insights into how these developments impact medical policies or reimbursement issues.
As he often cites data, sources that can offer credible statistics or research findings related to the evolving landscape of radiology at events like RSNA 2023 could capture his interest. Additionally, given his emphasis on private sector announcements and press releases, industry professionals with insider perspectives on new technologies or products are also likely to resonate with him.
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By: Erik L. Ridley
Editor's note: As part of the celebration of AuntMinnie.com's upcoming 25th anniversary, we're presenting 25 for 25 -- a series featuring our most popular content for each of the last 25 years. New articles will be published each Monday until our official anniversary at RSNA 2024. Our top article in 2014 reported on the financial benefits of health information exchanges.
The quality of radiology reports produced by residents can be quantitatively assessed, according to recent research.
BOSTON -- In a video interview at CMIMI 2024, Nina Kottler, MD, of Radiology Partners shares highlights from her keynote presentation on the clinical deployment of radiology AI. She reviews three key best practices and also offers some advice.
BOSTON -- A new method that utilizes probability data extracted from radiology reports for specific conditions could potentially assist in differential diagnosis, according to a Monday presentation at the Conference on Machine Intelligence in Medical Imaging (CMIMI).
A study presented at CMIMI 2024 showcased the potential for LLMs to aid in postdeployment monitoring of AI algorithms.
By: Erik L. Ridley
BOSTON -- We caught up with Eliot Siegel, MD, of the University of Maryland to discuss highlights so far from the Conference on Machine Intelligence in Medical Imaging (CMIMI), including the latest advances in large language models (LLMs).
By: Kate Madden Yee, Will Morton, Erik L. Ridley, Liz Carey, Amerigo Allegretto
Who made it to the final round in this year's edition of the Minnies, AuntMinnie's event recognizing excellence in radiology? See who our expert panelists selected as the final candidates in this year's event.
By: Erik L. Ridley
In 2020, our most highly viewed article reported on research that described how COVID-19 patients may initially present with non-respiratory symptoms.
By: Erik L. Ridley, Kate Madden, Will Morton, Amerigo Allegretto, Liz Carey
The presidential election may have ended last week in the U.S., but votes were still being counted for the 2024 edition of the Minnies.
Welcome to the first installment of this year’s Road to RSNA preview of the RSNA 2024 meeting. We’re once again providing a modality-by-modality overview of select scientific presentations to serve as your guide to events at McCormick Place.
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