Radiology AI News
AI Model Predicts EGFR Mutations From Pathology Slides in Lung Cancer
An AI model can accurately flag EGFR mutations in lung adenocarcinoma using routine pathology slides, reducing the need for rapid genetic tests.
AI System Estimates Bone Mineral Density from X-rays, Improves Osteoporosis Detection
Researchers have developed an AI-based system to estimate bone mineral density from lumbar and femur X-rays for early osteoporosis detection.
LLMs Demonstrate Potential for Fracture Classification in CT Radiology Reports
LLMs like ChatGPT-4o and AmbossGPT can accurately classify bone fractures in CT radiology reports, aiding radiologists.
AI Model Accurately Detects Cardiac Amyloidosis on Echocardiograms
An AI tool using echocardiograms accurately screens for cardiac amyloidosis, outperforming traditional detection methods.
LLMs Match Senior Doctors in Predicting Liver Cancer Therapy Outcomes
A study shows large language models can predict immunotherapy responses in liver cancer as accurately as experienced doctors.
SimonMed Imaging Debuts Two AI Mammography Services With Self-Pay Pricing
SimonMed Imaging launches Mammogram+ and Mammogram+ Heart AI-enhanced mammography services with out-of-pocket fees.
Study Finds AI Boosts Radiologists' Accuracy in Mammogram Readings
AI decision support improves radiologists' breast cancer detection accuracy when interpreting screening mammograms, mainly by enhancing focus on suspicious regions.
AI in Mammography Boosts Radiologists’ Focus and Accuracy
AI assistance enhances radiologists' breast cancer detection performance and directs attention to critical regions in mammograms.
Eye-Tracking Study Shows AI Support Enhances Radiologist Detection in Mammography
Radiologists using AI visual cues are more likely to identify breast cancers on mammograms, as revealed by eye-tracking analysis.
ChatGPT-Generated Questions Match Quality of Radiologist-Written MCQs for Residents
A study found that ChatGPT can generate multiple-choice questions for radiology residents of comparable quality to those written by attending radiologists.
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