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Representative radiographs (top), acquired in anteroposterior projection in the supine position, and corresponding attention maps (bottom). (A) Images show main diagnostic findings of the internal data set in a 49-year-old male patient with congestion, pneumonic infiltrates, and effusion (left); a 64-year-old male patient with congestion, pneumonic infiltrates, and effusion (middle); and a 69-year-old female patient with effusion (right). Image courtesy of Radiology.
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Check out our Cases of the Week!
66-year-old man with difficulty voiding
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Representative radiographs (top), acquired in anteroposterior projection in the supine position, and corresponding attention maps (bottom). (A) Images show main diagnostic findings of the internal data set in a 49-year-old male patient with congestion, pneumonic infiltrates, and effusion (left); a 64-year-old male patient with congestion, pneumonic infiltrates, and effusion (middle); and a 69-year-old female patient with effusion (right). Image courtesy of Radiology.
Artificial Intelligence
Can transformer models improve AI image interpretations?
Ultrasound
Ultrasound models show high marks in liver steatosis detection
CT
ASTRO: Are CT simulation scans needed for urgent palliation treatment?
Radiation Oncology/Therapy
ASTRO: Short radiation course improves head-and-neck cancer treatment
Representative radiographs (top), acquired in anteroposterior projection in the supine position, and corresponding attention maps (bottom). (A) Images show main diagnostic findings of the internal data set in a 49-year-old male patient with congestion, pneumonic infiltrates, and effusion (left); a 64-year-old male patient with congestion, pneumonic infiltrates, and effusion (middle); and a 69-year-old female patient with effusion (right). Image courtesy of Radiology.
Artificial Intelligence
Can transformer models improve AI image interpretations?
CT
Deep learning helps categorize acute appendicitis on pelvic CT
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Nanox touts CT study using its AI software
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ABMRS exams available online
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Radiobotics names new CEO
Breast
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Artificial Intelligence
Representative radiographs (top), acquired in anteroposterior projection in the supine position, and corresponding attention maps (bottom). (A) Images show main diagnostic findings of the internal data set in a 49-year-old male patient with congestion, pneumonic infiltrates, and effusion (left); a 64-year-old male patient with congestion, pneumonic infiltrates, and effusion (middle); and a 69-year-old female patient with effusion (right). Image courtesy of Radiology.
Can transformer models improve AI image interpretations?
A new class of AI appears to move the technology closer to what radiologists are capable of when they interpret chest x-rays.
Deep learning helps categorize acute appendicitis on pelvic CT
Nanox touts CT study using its AI software
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