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Magnetic resonance imaging of pelvic floor dysfunction - joint recomendations of the ESUR & ESGAR pelvic working group

Led by Rania Farouk El Sayed, this landmark consensus paper establishes the first international standardized protocols for MRI assessment of pelvic floor dysfunction (PFD). By unifying imaging techniques, measurements like the pubococcygeal line, and structured reporting, the study provides a vital framework for improving diagnostic accuracy and surgical planning in complex multi-compartment pelvic disorders.

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Artificial intelligence as an initial reader for double reading in breast cancer screening: A prospective initial study of 32,822 mammograms of the Egyptian population

In a landmark initiative for Egyptian healthcare, a groundbreaking study lead by Prof. Sahar Mansour has successfully integrated Artificial Intelligence (AI) into the national mammography screening process. Analyzing over 32,000 mammograms, the project achieved a remarkable 99.37% accuracy rate by pairing AI technology with radiologist expertise. This pioneer effort not only demonstrates the adaptability of AI across diverse populations but also marks a significant shift toward the future of early breast cancer detection and precision medicine in the Middle East and Africa.

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