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Background: Practice guidelines recommend patient management based on scientific evidence. Quality indicators gauge adherence to such recommendations and assess health care quality. They are usually defined as adverse event rates, which may not fully capture guideline adherence over time.

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Medical devices (MDs) play a critical role in healthcare delivery while also bringing potential medical risks and unintended harms to patients. Although government regulation is well recognized as a critical and essential function for ensuring the safety of MDs in many countries, the supplementary role that hospitals play is often neglected. This paper constructs a tripartite evolutionary game model involving the government, hospitals, and MDs enterprises to explore their strategic behaviors of MDs regulation in healthcare delivery.

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A recent study proposed a new genetic lineage of leatherback turtles (Dermochelys coriacea) based on genetic analysis, environmental history, and local ecological knowledge (LEK), suggesting the existence of two possible species or subspecies on the beaches of Oaxaca, diverging ~ 13.5 Mya. However, this hypothesis may be influenced by nuclear mitochondrial DNA segments (NUMTs), which could have been misamplified as true mtDNA.

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The expressway green channel is an essential transportation policy for moving fresh agricultural products in China. In order to extract knowledge from various records, this study presents a cutting-edge approach to extract information from textual records of failure cases in the vertical field of expressway green channel. We proposed a hybrid approach based on BIO labeling, pre-trained model, deep learning and CRF to build a named entity recognition (NER) model with the optimal prediction performance.

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To improve students' understanding of physical education teaching concepts and help teachers analyze students' cognitive patterns, the study proposes an association learning-based method for understanding physical education teaching concepts using deep learning algorithms, which extracts image features related to teaching concepts using convolutional neural networks. Moreover, a neurocognitive diagnostic model based on hypergraph convolution is constructed to mine the data of students' long-term learning sequences and identify students' cognitive outcomes. The findings revealed that the highest accuracy of the association graph convolutional neural network was 0.

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