BACKGROUND/OBJECTIVES: The clinical utility of body composition in the development of complications of acute pancreatitis (AP) remains unclear. We aimed to describe the associations between body composition and the recurrence of AP.
PURPOSE: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging.
RESEARCH QUESTION: Can artificial intelligence (AI)-powered annotation of numerous biological events help to uncover an association between embryonic kinetics and early pregnancy loss?
BACKGROUND: While predictive capabilities of machine learning (ML) algorithms for hip and knee total joint arthroplasty (TJA) have been demonstrated in previous studies, their performance in racial and ethnic minority patients has not been investigat...
AIMS: We aimed to create a predictive model utilizing machine learning (ML) to identify new cases of congestive heart failure (CHF) in individuals with diabetes in primary health care (PHC) through the analysis of diagnostic data.
BACKGROUND AND AIMS: The integrity of image acquisition is critical for biliopancreatic EUS reporting, significantly affecting the quality of EUS examinations and disease-related decision-making. However, the quality of EUS reports varies among endos...
The spine journal : official journal of the North American Spine Society
Oct 19, 2024
BACKGROUND CONTEXT: Longer posterior lumbar interbody fusion (PLIF) surgeries for individuals with lumbar spinal stenosis are linked to more complications and negatively affect recovery after the operation. Therefore, there is a critical need for a m...
PURPOSE: To validate the performance of autonomous diabetic retinopathy (DR) grading by comparing a human grader and a self-developed deep-learning (DL) algorithm with gold-standard evaluation.
INTRODUCTION: This study aimed to evaluate the role of deep learning methods in diagnosing foreign body aspiration (FBA) to reduce the frequency of negative bronchoscopy and minimize potential complications.
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