Artificial Intelligence

CNN models help determine best treatment for kids with GI obstructions
By Kate Madden Yee
Convolutional neural network (CNN) algorithms show promise for identifying gastrointestinal (GI) obstructions on x-ray in a pediatric population, researchers have reported.
February 28, 2025
Digestive System 3 D Intestine
ECR: Integrating AI into radiology workflows benefits the environment
By Kate Madden Yee
Sustainability in radiology is a hot topic at this year's ECR in Vienna, and a February 27 talk focused on "green" radiology using AI technology.
February 28, 2025
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ECR: Repurposed AI boosts breast cancer detection in diverse patient groups
By Amerigo Allegretto
Repurposed AI imaging tools can improve breast malignancy detection across diverse patient groups.
February 27, 2025
Artificial Intelligence Ai
ECR: Generative AI yields potential for assisting radiologists
By Amerigo Allegretto
Generative AI may have novel applications in the clinic, but using the technology comes with its share of challenges and future directions.
February 26, 2025
Marc Kohli, MD, discusses current and potential future uses of generative AI in radiology at ECR 2025 in Vienna, Austria. Behind him is an image created by one such generative AI model, which illustrates humans working alongside AI.
LLM Mistral rivals GPT-4 Turbo for extracting clinical history elements
By Liz Carey
Mistral outperformed Llama and GPT-4 Turbo in a real-world application that assessed the completeness of clinical histories accompanying radiology imaging orders from the emergency department.
February 25, 2025
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AI helps predict kidney function decline in Lu-177 patients
By Will Morton
An open-source AI tool can help predict renal function decline in prostate cancer patients undergoing lutetium-177 (Lu-177) radiopharmaceutical therapy.
February 25, 2025
An axial CT image illustrating segmentation of functioning kidney tissue (blue areas), excluding kidney cysts and renal pelvis, using TotalSegmentator. Image and caption courtesy of RSNA.
What's best practice for using AI for thoracic imaging?
By Kate Madden Yee
The use of AI in thoracic imaging has begun to demonstrate "cumulative evidence of effectiveness," but more testing and research are needed to determine its feasibility for this application.
February 25, 2025
Lung Ct Images
T2-weighted MRI shows promise for body composition analysis
By Kate Madden Yee
Using deep learning with T2-weighted MR imaging is a feasible way to assess patients' body composition, researchers have reported.
February 21, 2025
Fat Tissue Adipocytes
Enlitic, Laitek ink data migration support agreement with GEHC
By AuntMinnie.com staff writers
Enlitic and subsidiary Laitek have signed an agreement with GE HealthCare to support data migration across GE HealthCare’s delivery networks.
February 18, 2025
Artificial Intelligence Ai Medical Healthcare Tools 400
Public trust in medical AI use low
By Amerigo Allegretto
Trust is low among U.S. adults when it comes to healthcare systems using AI responsibly and protecting patients from AI-related harms.
February 14, 2025
Artificial Intelligence Ai Data
Can LLMs help improve oncologic imaging interpretation?
By Erik L. Ridley
A large-language model was found to significantly improve the quality of patient clinical histories for oncologic imaging requisitions.
February 4, 2025
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Using AI with mammography can help select women for breast MRI
By Amerigo Allegretto
Using AI with mammography can help select women at high risk of breast cancer for supplemental MRI.
February 4, 2025
Images depict a 55-year-old woman with a family history of breast cancer who underwent combined mammography and MRI screening. (A) Right and (B) left mediolateral oblique and (C) right and (D) left craniocaudal mammograms show a large known cyst in the left breast (arrow in B and D), but were otherwise assessed as being unremarkable. Breast tissue was judged to be extremely dense. (E) Concurrent axial subtraction MRI scan shows a large, diffuse, invasive lobular cancer (circle) in the right breast. The AI system provided a case-based cancer suspicion score of 8 on a scale of 0-10, which would have led to selection for MRI screening using both the score 5 and score 8 thresholds, but not the score 9 threshold.
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