Relationship between Ambulatory Pulse Pressure, Pulse Pressure Index and Coronary Artery Disease in Patients with Hypertension

Objective: To analyze the relationship between ambulatory pulse pressure, pulse pressure index, and coronary artery disease in patients with hypertension. Methods: From February 2018 to February 2019, a group of 100 patients with hypertension (control group) and a group of 100 patients with hypertension and coronary artery disease (experimental group) were selected to monitor and analyze dynamic pulse pressure and pulse pressure indicators. Results: In terms of clinical indicators, values of NPPI, 24hPP and 24hPPI in the experimental group were significantly higher than those in the control group. P < 0.05 indicates that there is statistical value in the data difference. Conclusion: In the clinical diagnosis of hypertension patients, ambulatory pulse pressure, pulse pressure index are highly correlated with the risk of coronary artery disease. Therefore, researchers should actively pay attention to the relevant indicators of patients to lay a solid foundation for the effective protection of patients’ health

Efficacy Assessment of Emergency Percutaneous Coronary Intervention (PCI) for Acute Myocardial Infarction (AMI)

Objective: To assess the clinic effect of percutaneous coronary intervention in the treatment of acute myocardial infarction. Methods: 90 patients with acute myocardial infarction in our hospital were chosen to be research objects and they were divided into two groups: control group and research group. Patients in control group were only treated by thrombolytic therapy while those in research group were further treated by percutaneous coronary intervention on the basis of this treatment. Result: The efficacy of research group was higher than that in control group. The incidence of adverse events was 4.44%, which is lower than that in control group. Conclusion: We should effectively apply percutaneous coronary intervention in treating acute myocardial infarction so as to improve the cardiac function of the patients. In addition, this treatment is safer and will lower the incidence of heart and renal failure

Let Images Give You More:Point Cloud Cross-Modal Training for Shape Analysis

Although recent point cloud analysis achieves impressive progress, the paradigm of representation learning from a single modality gradually meets its bottleneck. In this work, we take a step towards more discriminative 3D point cloud representation by fully taking advantages of images which inherently contain richer appearance information, e.g., texture, color, and shade. Specifically, this paper introduces a simple but effective point cloud cross-modality training (PointCMT) strategy, which utilizes view-images, i.e., rendered or projected 2D images of the 3D object, to boost point cloud analysis. In practice, to effectively acquire auxiliary knowledge from view images, we develop a teacher-student framework and formulate the cross modal learning as a knowledge distillation problem. PointCMT eliminates the distribution discrepancy between different modalities through novel feature and classifier enhancement criteria and avoids potential negative transfer effectively. Note that PointCMT effectively improves the point-only representation without architecture modification. Sufficient experiments verify significant gains on various datasets using appealing backbones, i.e., equipped with PointCMT, PointNet++ and PointMLP achieve state-of-the-art performance on two benchmarks, i.e., 94.4% and 86.7% accuracy on ModelNet40 and ScanObjectNN, respectively. Code will be made available at https://github.com/ZhanHeshen/PointCMT.Comment: To appear in NIPS202