Publications by authors named "B Rizk"

Article Synopsis
  • The study evaluates a new algorithm designed for personalized contrast injection during liver CT scans to enhance imaging quality while ensuring patient safety.
  • Data was collected from 384 adult patients undergoing abdominal CT for cancer staging or follow-up, utilizing a web interface to customize the contrast injection based on individual characteristics.
  • Results showed that the algorithm consistently achieved liver enhancement centered at 50 HU across different patient demographics, reinforcing its potential to improve diagnostic accuracy in personalized medicine.
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Article Synopsis
  • - High ovarian response to stimulation is identified by having more than 18-20 follicles or oocytes, indicating a risk for complications like ovarian hyper-stimulation syndrome (OHSS).
  • - Diagnosis of high response can occur before or after oocyte retrieval, and is influenced by ovarian reserve markers like AMH and AFC, especially in women with PCOS.
  • - Effective management strategies involve personalized treatment plans based on monitoring, which can help reduce the risk of OHSS for those identified as high responders.
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Carbonaceous asteroids, such as (101955) Bennu, preserve material from the early Solar System, including volatile compounds and organic molecules. We report spacecraft imaging and spectral data collected during and after retrieval of a sample from Bennu's surface. The sampling event mobilized rocks and dust into a debris plume, excavating a 9-meter-long elliptical crater.

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When the OSIRIS-REx spacecraft pressed its sample collection mechanism into the surface of Bennu, it provided a direct test of the poorly understood near-subsurface physical properties of rubble-pile asteroids, which consist of rock fragments at rest in microgravity. Here, we find that the forces measured by the spacecraft are best modeled as a granular bed with near-zero cohesion that is half as dense as the bulk asteroid. The low gravity of a small rubble-pile asteroid such as Bennu effectively weakens its near subsurface by not compressing the upper layers, thereby minimizing the influence of interparticle cohesion on surface geology.

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Objectives: To develop a deep-learning algorithm for anterior cruciate ligament (ACL) tear detection and to compare its accuracy using two external datasets.

Methods: A database of 19,765 knee MRI scans (17,738 patients) issued from different manufacturers and magnetic fields was used to build a deep learning-based ACL tear detector. Fifteen percent showed partial or complete ACL rupture.

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