The purpose of this study was to develop a fully automated and reliable volumetry of the cerebellum of children during infancy and childhood using deep learning algorithms in comparison to manual segmentation. In addition, the clinical usefulness of ...
Monoclonal antibodies (mAbs) can be damaged during the aseptic compounding process, with aggregation being the most prevalent form of degradation. Protein aggregates represent one of several risk factors for undesired immunogenicity of mAbs, which ca...
In this paper, we present a novel algorithm that uses machine learning and natural language processing techniques to facilitate the coding of feature listing data. Feature listing is a method in which participants are asked to provide a list of featu...
Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation
Oct 13, 2023
OBJECTIVE: The American Medical Association recommends health information to be written at a 6th grade level reading level. Our aim was to determine whether Artificial Intelligence can outperform the existing health information on kidney stone preven...
AIM: To investigate the effect of deep learning on the diagnostic performance of radiologists and radiology residents in detecting breast cancers on computed tomography (CT).
Journal of gastroenterology and hepatology
Oct 13, 2023
BACKGROUND AND AIM: Convolutional neural network (CNN) systems that automatically detect abnormalities from small-bowel capsule endoscopy (SBCE) images are still experimental, and no studies have directly compared the clinical usefulness of different...
BACKGROUND: We are currently experiencing a third digital revolution driven by artificial intelligence (AI), and the emergence of new chat generative pre-trained transformer (ChatGPT) represents a significant technological advancement with profound i...
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