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RSNA Unveils 10 Most Cited Radiology Studies of 2023

By MedImaging International staff writers
Posted on 20 Dec 2023
Image: RSNA has released a list of the 10 most-cited academic papers published in 2023 (Photo courtesy of RSNA)
Image: RSNA has released a list of the 10 most-cited academic papers published in 2023 (Photo courtesy of RSNA)

The Radiological Society of North America (RSNA, Oak Brook, IL, USA) has released a list of the 10 most-cited academic papers published in 2023 in its 100-year-old journal, Radiology. The list offers insight into the currently popular trends in the field of imaging, in terms of what researchers are working on and what is being covered by the media.

The following studies published in Radiology were cited the most in 2023:

1) ChatGPT and Other Large Language Models Are Double-edged Swords.

2) ChatGPT and the Future of Medical Writing.

3) ChatGPT Is Shaping the Future of Medical Writing But Still Requires Human Judgment.

4) Leveraging GPT-4 for Post Hoc Transformation of Free-text Radiology Reports into Structured Reporting: A Multilingual Feasibility Study.

5) Supplemental Breast Cancer Screening in Women with Dense Breasts and Negative Mammography: A Systematic Review and Meta-Analysis.

6) Appropriateness of Breast Cancer Prevention and Screening Recommendations Provided by ChatGPT.

7) FAPI PET: Fibroblast Activation Protein Inhibitor Use in Oncologic and Nononcologic Disease.

8) Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.

9) AI Improves Nodule Detection on Chest Radiographs in a Health Screening Population: A Randomized Controlled Trial.

10) Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

The list indicates that ChatGPT, and its underlying AI model GPT-4, were dominating research trends. The chatbot developed by OpenAI is highly popular with everyone and had 185 million users as of December 2023. At RSNA 2023 held in Chicago, the focus was mainly on AI and its increasing number of applications and vendors, most of which were related to emerging research. The RSNA’s announcement provides additional details, including a list of the most downloaded research papers.

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Image: Researchers develop a vision-language model trained on large-scale data to generate clinically relevant findings from chest computed tomography images through visual question answering (Ms. Maiko Nagao from Meijo University, Japan)

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