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Road to RSNA 2023: AI Preview

AuntMinnie

Welcome to the first installment of this year’s Road to RSNA preview of the RSNA 2023 meeting. AI’s capability and potential to enhance the practice of radiology will take center stage at RSNA 2023. For more information on those presentations and other abstracts, check out the RSNA 2023 meeting program. 9:40 a.m. | 9:40 a.m. |

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Minnies winners for 2023 highlight AI, innovation in radiology

AuntMinnie

And 2023 is no exception. The technology figured prominently in five Minnies categories, including Hottest Clinical Procedure. Workforce shortages were deemed by our Expert Panel to be the biggest threat in 2023. Menias’ clinical focus has been geared to patient-centered care, and she’s absolutely unwavering.

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3 AI-based technology trends on display at the 2023 RSNA conference

AuntMinnie

At RSNA 2023, look for AI-driven systems that radiographers can use to help make patient positioning faster and more precise, and bring consistency to the process, all of which help improve image quality and reduce the need for retakes. Even the most skilled radiographers can fail to get positioning just right.

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Who’s Reading My Chest X-ray?

Everything Rad

RT (R)(T) | Clinical Applications Specialist, Carestream The U.S. This program trains and certifies physicians to read chest radiographs for workers participating in health surveillance programs. Radiologists complete over 20,000 hours of clinical experience before being certified to interpret radiographic images.

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Meet the Minnies 2024 finalists

AuntMinnie

Most Influential Radiology Researcher Erik Middlebrooks, MD, Mayo Clinic, Jacksonville, FL Erik Middlebrooks, MD. One of this year's nominations for Most Influential Radiology Researcher is Erik Middlebrooks, MD, of the Mayo Clinic in Jacksonville, FL. Elliot Fishman, MD.

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Deep-Learning Chest Radiograph Model Predicts Mortality for Community-Acquired Pneumonia

Imaging Technology

The deep learning (DL) model may guide clinical decision-making in the management of patients with CAP by identifying high-risk patients who warrant hospitalization and intensive treatment,” concluded first author Eui Jin Hwang, MD, PhD, from the department of radiology at Seoul National University College of Medicine in Korea. Hwang et al.

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AI assist for x-ray reads serves nonradiologists well in the ED

AuntMinnie

Presenting the research on November 28 at RSNA 2023, Jan Rudolph, MD, from the department of radiology at University Hospital LMU Munich said nonradiologists can significantly benefit from AI assistance in emergency-related chest x-ray analysis. “So

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