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Navigating the future of mammography: How women's perceptions of AI may guide tomorrow's screening practice.
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Department of Medical Imaging and Physiology, Skåne University Hospital, Inga Marie Nilssons gata 47 205 02, Malmö, Sweden; Department of Translational Medicine, Diagnostic Radiology, Lund University, Inga Marie Nilssons gata 47 205 02, Malmö, Sweden.
Hair Today, OR Tomorrow: A Multicenter Case Series of Gastric Bezoars in Children Diagnosed With Point-of-Care Ultrasound.
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Division of Pediatric Emergency Medicine, Department of Emergency Medicine, Columbia University Irving Medical Center, New York, NY.
Point-of-care ultrasound (POCUS) can expedite the diagnosis of pediatric abdominal pathologies including appendicitis and intussusception. In this patient series, we present cases from multiple pediatric emergency departments that demonstrate the use of POCUS in the diagnosis of trichobezoars in children. POCUS findings include the presence of an intragastric hyperechoic mass or a hyperechoic arch and associated posterior acoustic shadowing.
View Article and Find Full Text PDFLow-Temperature NO Gas-Sensing System Based on Metal-Organic Framework-Derived InO Structures and Advanced Machine Learning Techniques.
Inorg Chem
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School of Materials Science and Engineering, Jiangsu University, Zhenjiang 212013, China.
In the bustling metropolis of tomorrow, where pollution levels are a constant concern, a team of innovative researchers embarked on a quest to revolutionize air quality monitoring. In pursuit of this objective, this study embarked on the synthesis of indium oxide materials via a straightforward solvothermal method purposely for NO detection. Through meticulous analysis of their gas-sensing capabilities, a remarkable discovery came to light.
View Article and Find Full Text PDFAI Applications to Breast MRI: Today and Tomorrow.
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Department of Radiology, Memorial Sloan Kettering Cancer Center, New York City, New York, USA.
In breast imaging, there is an unrelenting increase in the demand for breast imaging services, partly explained by continuous expanding imaging indications in breast diagnosis and treatment. As the human workforce providing these services is not growing at the same rate, the implementation of artificial intelligence (AI) in breast imaging has gained significant momentum to maximize workflow efficiency and increase productivity while concurrently improving diagnostic accuracy and patient outcomes. Thus far, the implementation of AI in breast imaging is at the most advanced stage with mammography and digital breast tomosynthesis techniques, followed by ultrasound, whereas the implementation of AI in breast magnetic resonance imaging (MRI) is not moving along as rapidly due to the complexity of MRI examinations and fewer available dataset.
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