The purpose is to realize the intelligent reform of piano online teaching and the intelligent optimization of wireless networks. Empirical research is realized with quantitative research and algorithm simulation as the starting point. First, regression fitting algorithm and Relief F weight algorithm are adopted to extract the effectiveness of each characteristic variable. Next, under the guidance of metric learning theory, K-Nearest Neighbors (KNN) in Projected Feature Space (P-KNN) algorithm is proposed to complete the hierarchical recognition of piano teaching influence features. Metric Learning With Support Vector Machine (ML-SVM) classification algorithm is employed to identify the feature performance affecting piano teaching. Finally, the performance of P-KNN algorithm and ML-SVM algorithm is compared with KNN algorithm and Information-Theoretic-Metric-Learning (ITML) algorithm. It is concluded that the recognition accuracies of P-KNN and ML-SVM are 82.78% and 83.97%, respectively. Based on the quantitative research on the characteristics affecting piano teaching, artificial intelligence and wireless network optimization are combined to explore the implementation path of intelligent technology in piano teaching reform, reflect the use value of modern science and technology in piano teaching, and innovate the process of music online education reform of piano teaching.
BackgroundCongenital diaphragmatic hernia (CDH) is a scarce birth defect. It is called late-presenting CDH when symptoms are found after 1 month of life. The clinical manifestations of late-presenting CDH are diverse, among which the most fatal is the cardiac arrest caused by tension gastrothorax. The disease is rare, can easily lead to death owing to improper emergency treatment. This report illustrates the emergency treatment of late-presenting CDH with tension gastrothorax in three Chinese children.Case reports and managementThree children presented to emergency room with a sudden dyspnea, diagnosed accurately by x-ray or computed tomography. In case 1, the gastric tube could not be inserted at the first attempt, and the child cried incessantly. Cardiac arrest occurred when the gastric tube was re-inserted. After cardiopulmonary resuscitation and placement of a thoracic drainage tube, a large amount of gas and stomach contents were drained. Laparoscopic surgery was performed. The patient died of sepsis. In case 2, the gastric tube could not be inserted at the first attempt; consequently, emergency surgery was considered instead of retrying. After the patient was anesthetized, a gastric tube was successfully placed. Subsequently, a large amount of gas and gastric contents was drained, and thoracoscopic surgery was performed. The patient recovered evenly. In case 3, the gastric tube was successfully inserted at the first attempt; however, the vital signs were unstable due to poor drainage of the gastric tube. We injected 20 ml of iohexol into the stomach tube for angiography and dynamic chest film monitoring. After adjusting the position of the stomach tube, the stomach collapsed completely. Thoracoscopic surgery was performed. The patient recovered evenly.ConclusionEarly diagnosis is essential for children with late-presenting CDH complicated by tension gastrothorax. Fully collapsing the stomach is a key step in emergency treatment. In addition, gastric tube insertion is the first choice. In children with difficulty in gastric tube placement at the first attempt, the gastric tube can be placed under anesthesia, and emergency surgery performed simultaneously. Endoscopic surgery can be the first choice in cases of complete stomach collapse.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.