Results 81 to 90 of about 143,960 (307)
Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays [PDF]
arXiv, 2019 Chest X-rays are the most common diagnostic exams in emergency rooms and hospitals. There has been a surge of work on automatic interpretation of chest X-rays using deep learning approaches after the availability of large open source chest X-ray dataset from NIH.
arxiv
COVID-19 Detection in Chest X-ray Images Using Swin-Transformer and Transformer in Transformer [PDF]
arXiv, 2021 The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damage. Chest X-ray images are widely used for COVID-19 diagnosis and the Artificial Intelligence method can increase efficiency and accuracy. In the Challenge of Chest XR COVID-19 detection in Ethics and Explainability for Responsible Data Science (EE-RDS) conference 2021 ...
arxiv
Advanced Healthcare Materials, Volume 14, Issue 13, May 16, 2025.Nanobubbles functionalized with indocyanine green and ischemic myocardium‐targeting peptide effectively target cardiomyocytes and enable the multimodal (fluorescence, ultrasonic, and photoacoustic) imaging of ischemic myocardium in mice with coronary microvascular dysfunction (CMD).
Bo Yu +8 more
wiley +1 more source
مراقبت پرستاری و مامایی ابن سینا, 2018 Introduction: The removal of the chest tube drainage is a painful experience for patients. Painless pain and patient's discomfort is associated with reduced chest dilatation, respiratory dysfunction with hypoxemia, increased sympathetic response to ...
Mohamad Mehdi Hatami +4 more
doaj
Hazardous Removal of a Misplaced Nasogastric Tube
Journal of the Belgian Society of Radiology, 2020 Teaching point: Careful analysis of tubes positioning on chest X-ray not only reveals misplacement but also helps to plan a safe removal.
Jean-Philippe Hardy +2 more
doaj +1 more source
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays [PDF]
arXiv, 2020 The use of smartphones to take photographs of chest x-rays represents an appealing solution for scaled deployment of deep learning models for chest x-ray interpretation. However, the performance of chest x-ray algorithms on photos of chest x-rays has not been thoroughly investigated. In this study, we measured the diagnostic performance for 8 different
arxiv
Pattern and Outcome of Chest Injuries at Bugando Medical Centre in Northwestern Tanzania. [PDF]
, 2011 Chest injuries constitute a continuing challenge to the trauma or general surgeon practicing in developing countries. This study was conducted to outline the etiological spectrum, injury patterns and short term outcome of these injuries in our setting ...
A Kalliopi +39 more
core +2 more sources
Materials Advances in Devices for Heart Disease Interventions
Advanced Materials, EarlyView.This review examines the crucial role of materials in heart disease interventions, focusing on strategies for monitoring, managing, and repairing heart conditions. It discusses the material requirements for medical devices, highlighting recent innovations and their impact on cardiovascular health.
Gagan K. Jalandhra +11 more
wiley +1 more source
Airway segmentation from 3D chest CT volumes based on volume of interest using gradient vector flow [PDF]
arXiv, 2017 Some lung diseases are related to bronchial airway structures and morphology. Although airway segmentation from chest CT volumes is an important task in the computer-aided diagnosis and surgery assistance systems for the chest, complete 3-D airway structure segmentation is a quite challenging task due to its complex tree-like structure.
arxiv
Simulation as Staff Development for Competency in Nursing Care of Patients with Chest Tubes [PDF]
, 2016 There is an estimated 98,000 to 400,000 hospital errors that result in patient harm or death annually (David, Gunnarsson, Waters, Horblyuk and Kaplan, 2013; James 2013).
Dent, Jennifer
core +1 more source