Breast cancer continues to drive demand for precise, scalable diagnostics. A recent artificial intelligence framework brings together segmentation, feature extraction and classifi
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Prostate MRI is increasingly used within organised testing pathways to improve prostate cancer diagnostics while limiting overdiagnosis linked to systematic biopsy approaches. As imaging be
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Low-dose computed tomography (LDCT) has expanded lung cancer screening (LCS) but increased pressure on radiology services. An automated artificial intelligence approach was evaluated a
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Thyroid nodules are among the most frequent findings in diagnostic imaging, often discovered incidentally during scans of the neck or chest. While most nodules are benign, determining&
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Accurate evaluation of liver function is essential in chronic liver disease, cirrhosis and preoperative planning. Clinicians often rely on blood tests and scores such as Albumin–Bilirubin g
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Growing demand for brain MRI and limited reporting capacity are increasing delays in imaging workflows and heightening concern about error risk. A self-supervised text–vision framework addr
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Accurate brain tumour identification and segmentation are critical for early diagnosis, tailored treatment and improved survival outcomes. However, structural variabilit
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Contrast-enhanced mammography (CEM) supplies two complementary views of the breast: mammographic density (MD), which reflects anatomical features, and background parenchymal enhancement (BP
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Growing imaging demand and the complexity of interventional stroke documentation place sustained pressure on radiology workflows. Mechanical thrombectomy reports contain technical
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Emergency radiology (ER) has developed into a distinct subspecialty embedded in acute care, yet its organisation differs across health systems. A cross-national survey examined ho
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