Patient's airway monitoring during cardiopulmonary resuscitation using deep networks.

Cardiopulmonary resuscitation (CPR) is a crucial life-saving technique commonly administered to individuals experiencing cardiac arrest. Among the important aspects of CPR is ensuring the correct airway position of the patient, which is typically monitored by human tutors or supervisors. This study aims to utilize deep transfer learning for the detection of the patient's correct and incorrect airway position during cardiopulmonary resuscitation.

Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT.

Supervised deep learning has become a standard approach to solving medical image segmentation tasks. However, serious difficulties in attaining pixel-level annotations for sufficiently large volumetric datasets in real-life applications have highlighted the critical need for alternative approaches, such as semi-supervised learning, where model training can leverage small expert-annotated datasets to enable learning from much larger datasets without laborious annotation. Most of the semi-supervised approaches combine expert annotations and machine-generated annotations with equal weights within deep model training, despite the latter annotations being relatively unreliable and likely to affect model optimization negatively.

Learning-to-augment incorporated noise-robust deep CNN for detection of COVID-19 in noisy X-ray images.

Deep convolutional neural networks (CNNs) are used for the detection of COVID-19 in X-ray images. The detection performance of deep CNNs may be reduced by noisy X-ray images. To improve the robustness of a deep CNN against impulse noise, we propose a novel CNN approach using adaptive convolution, with the aim to ameliorate COVID-19 detection in noisy X-ray images without requiring any preprocessing for noise removal.

Internet of things in the management of chronic diseases during the COVID-19 pandemic: A systematic review.

Introduction: The use of new technologies such as the Internet of Things (IoT) in the management of chronic diseases, especially in the COVID pandemics, could be a life-saving appliance for public health practice. The purpose of the current study is to identify the applications and capability of IoT and digital health in the management of the COVID-19 pandemic.

Methods: This systematic review was conducted by searching the online databases of PubMed, Scopus, and Web of Science using selected keywords to retrieve the relevant literature published until December 25th, 2021.

Greedy Autoaugment for classification of mycobacterium tuberculosis image via generalized deep CNN using mixed pooling based on minimum square rough entropy.

Although tuberculosis (TB) is a disease whose cause, epidemiology and treatment are well known, some infected patients in many parts of the world are still not diagnosed by current methods, leading to further transmission in society. Creating an accurate image-based processing system for screening patients can help in the early diagnosis of this disease. We provided a dataset containing1078 confirmed negative and 469 positive Mycobacterium tuberculosis instances.

Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images.

Chest X-ray images are used in deep convolutional neural networks for the detection of COVID-19, the greatest human challenge of the 21st century. Robustness to noise and improvement of generalization are the major challenges in designing these networks. In this paper, we introduce a strategy for data augmentation using the determination of the type and value of noise density to improve the robustness and generalization of deep CNNs for COVID-19 detection.

Comparing the Effects of Pulsatile and Continuous Flushing on Time and Type of Peripheral Intravenous Catheters Patency: A Randomized Clinical Trial.

Peripheral intravenous catheters (PICs) patency techniques such as flushing are being developed. According to some studies, flushing can be used continuously or in pulsatile forms. This study aimed to compare the effects of pulsatile flushing (PF) and continuous flushing (CF) on time and type of PICs patency.

Comparison of Using Cold Versus Regular Temperature Tube on Successful Nasogastric Intubation for Patients in Toxicology Emergency Department: a Randomized Clinical Trial.

In view of the contradictory results for the use of cold tubes for the purpose of enhancing nasogastric tube insertion success there is a pressing need for further research in this area. This study aimed to determine the effect of using cold versus regular temperature nasogastric tube on successful nasogastric tube insertion for patients referring to toxicology emergency department. This study is a clinical trial with two groups design of 65 patients admitted to toxicology emergency department who were divided into two groups by random allocation.