Image Interpretation Public Health Radiologist 
AuntMinnie
JULY 10, 2023
The rate of diagnostic imaging interpretation by nonphysician practitioner. Read more on AuntMinnie.com Related Reading: ED nonphysician practitioners boost imaging use Expanded authorization for nonphysician providers What awaits radiologists when the public health emergency ends?
Imaging Technology
NOVEMBER 14, 2024
The American College of Radiology (ACR), a professional medical society representing radiologists, has also joined the Healthcare AI Challenge Collaborative as a founding member to ensure its 42,000 members have access to the Healthcare AI Challenge.
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AuntMinnie
OCTOBER 2, 2024
tesla MRI AI body composition analysis Cardiac PET Cryo/thermoablation CT colonography Genicular artery embolization Hyperpolarized xenon-129 MRI PET/MRI Photon-counting CT Radiomics Theranostics Whole-body MRI screening Image of the Year 3D PET/MR image. Radiologist Workforce Attrition from 2019 to 2024: A National Medicare Analysis.
Vesta Teleradiology
FEBRUARY 12, 2025
This technology mitigates the challenges posed by a shortage of on-site radiologists and enhances the quality of care in remote areas. A report from Healthcare IT News highlights how teleradiology enables radiologists to interpret scans remotely, increasing flexibility in work schedules and expanding access to specialized expertise.
AuntMinnie
OCTOBER 3, 2024
Researchers led by Solveig Hofvind, PhD, from the Norwegian Institute of Public Health in Oslo found that absolute average AI scores based on commercially available algorithms were higher for breasts developing cancer versus not developing cancer four to six years before their eventual detection on screening mammography.
Future Teleradiology
NOVEMBER 22, 2023
Enhanced Image Interpretation with Deep Learning: Discuss the potential of deep learning algorithms in revolutionizing image interpretation. Explore how AI-driven deep learning models can augment radiologists’ diagnostic accuracy by recognizing intricate patterns and subtle abnormalities.
Aidoc
AUGUST 1, 2024
By analyzing community health data, machine learning models can identify potential health threats and track habits that contribute to disease proliferation. This proactive approach enables early intervention, ultimately reducing the burden on healthcare systems and improving public health outcomes.
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