Deep Learning-Based Postoperative Recovery and Nursing of Total Hip Arthroplasty.

Objective: To develop a deep learning-assisted recovery and nursing system after total hip arthroplasty and to conduct clinical trials in order to verify its accuracy.

Methods: In our study, based on manual labeling, the human hip X-ray image library was established, and the deep neural network based on Mask R-CNN was built. The labeled medical images were used to train the model, providing reference for nursing decision after hip replacement.

Cepharanthine ameliorates titanium particle-induced osteolysis by inhibiting osteoclastogenesis and modulating OPG/RANKL ratio in a murine model.

Periprosthetic asepteic loosening, caused by wear debris, is one of the most severe complications, generally resulting in implant failure. Extensive osteoclast formation and activation are considered as the cause for periprosthetic osteolysis. However, few approaches have been approved to be used for preventing early-stage periprosthetic osteolysis.

Perceptions of Reducing Tube Feeding for Persons with Advanced Dementia among Various Professions in a Teaching Hospital.

Background: Even though no evidence suggests tube feeding is beneficial for individuals with advanced dementia, many are still tube fed.

Objective: To assess perceptions of hospital staff regarding reducing tube feeding (RTF) of patients with advanced dementia.

Design: Cross-sectional survey.

Associations between Respiratory Diseases and Dietary Patterns Derived by Factor Analysis and Reduced Rank Regression.

Background/aims: The study aims to identify children's dietary patterns and explore the relationship between dietary patterns and respiratory diseases.

Methods: Subjects were 2,397 fourth graders in 14 Taiwanese communities who participated in the Taiwan Children Health Study. This study is based on an evaluation of dietary patterns, performed from April until June 2011.