Introduction: Fatty liver disease (FLD) is associated with systemic inflammation, metabolic disease, and socioeconomic risk factors for poor health outcomes. Little is known on how adults with FLD recover from traumatic injury.
Methods: We studied adults admitted to the intensive care unit of a level 1 trauma center (2016-2020), excluding severe head injury/cirrhosis (N = 510).
Rationale And Objectives: Spinal osteoporotic compression fractures (OCFs) can be an early biomarker for osteoporosis but are often subtle, incidental, and underreported. To ensure early diagnosis and treatment of osteoporosis, we aimed to build a deep learning vertebral body classifier for OCFs as a critical component of our future automated opportunistic screening tool.
Materials And Methods: We retrospectively assembled a local dataset, including 1790 subjects and 15,050 vertebral bodies (thoracic and lumbar).
Unlabelled: Currently, there is no reproducible, widely accepted gold standard to classify osteoporotic vertebral body fractures (OVFs). The purpose of this study is to refine a method with clear rules to classify OVFs for machine learning purposes. The method was found to have moderate interobserver agreement that improved with training.
View Article and Find Full Text PDFPurpose: Advanced imaging examinations of emergently transferred patients (ETPs) are overread to various degrees by receiving institutions. The practical clinical impact of these second opinions has not been studied in the past. The purpose of this study is to determine if emergency radiology overreads change emergency medicine decision making on ETPs in the emergency department (ED).
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