Deep Learning-Based Diagnosis Algorithm for Alzheimer's Disease.

Alzheimer's disease (AD), a degenerative condition affecting the central nervous system, has witnessed a notable rise in prevalence along with the increasing aging population. In recent years, the integration of cutting-edge medical imaging technologies with forefront theories in artificial intelligence has dramatically enhanced the efficiency of identifying and diagnosing brain diseases such as AD. This paper presents an innovative two-stage automatic auxiliary diagnosis algorithm for AD, based on an improved 3D DenseNet segmentation model and an improved MobileNetV3 classification model applied to brain MR images.

Niacin Improves Intestinal Health through Up-Regulation of AQPs Expression Induced by GPR109A.

(1) Background: Changes in the expression of aquaporins (AQPs) in the intestine are proved to be associated with the attenuation of diarrhea. Diarrhea is a severe problem for postweaning piglets. Therefore, this study aimed to investigate whether niacin could alleviate diarrhea in weaned piglets by regulating AQPs expression and the underlying mechanisms; (2) Methods: 72 weaned piglets (Duroc × (Landrace × Yorkshire), 21 d old, 6.

The Learning-based Automatic Segmentation Algorithm of Brain MR Images Based on 7T.

Background: The learning-based algorithms provide an ability to automatically estimate and refine GM, WM and CSF. The ground truth manually achieved from the 3T MR image may not be accurate and reliable with poor image intensity contrast. It will seriously influence the classification performance because the supervised learning-based algorithms extremely rely on the ground truth.