AIMC Topic: Pulmonary Embolism
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CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.
Medical physics
Jun 21, 2022
BACKGROUND: The morbidity of pulmonary embolism (PE) is only lower than that of coronary heart disease and hypertension. Early detection, early diagnosis, and timely treatment are the keys to effectively reduce the risk of death. Nevertheless, PE seg...
Massive external validation of a machine learning algorithm to predict pulmonary embolism in hospitalized patients.
Thrombosis research
Jun 2, 2022
BACKGROUND: Pulmonary embolism (PE) is a life-threatening condition associated with ~10% of deaths of hospitalized patients. Machine learning algorithms (MLAs) which predict the onset of pulmonary embolism (PE) could enable earlier treatment and impr...
Current imaging of PE and emerging techniques: is there a role for artificial intelligence?
Clinical imaging
May 10, 2022
Acute pulmonary embolism (PE) is a critical, potentially life-threatening finding on contrast-enhanced cross-sectional chest imaging. Timely and accurate diagnosis of thrombus acuity and extent directly influences patient management, and outcomes. Te...
Automated detection of pulmonary embolism from CT-angiograms using deep learning.
BMC medical imaging
Mar 14, 2022
BACKGROUND: The aim of this study was to develop and evaluate a deep neural network model in the automated detection of pulmonary embolism (PE) from computed tomography pulmonary angiograms (CTPAs) using only weakly labelled training data.
Nursing Intervention Countermeasures of Robot-Assisted Laparoscopic Urological Surgery Complications.
Contrast media & molecular imaging
Nov 30, 2021
The objective is to explore the application effect of comprehensive nursing intervention in prevention of lower extremity deep vein thrombosis and pulmonary embolism in urological patients undergoing laparoscopic and robot-assisted laparoscopic surge...
Performance of a 3D convolutional neural network in the detection of hypoperfusion at CT pulmonary angiography in patients with chronic pulmonary embolism: a feasibility study.
European radiology experimental
Sep 24, 2021
BACKGROUND: Chronic pulmonary embolism (CPE) is a life-threatening disease easily misdiagnosed on computed tomography. We investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed t...
Present Limitations of Artificial Intelligence in the Emergency Setting - Performance Study of a Commercial, Computer-Aided Detection Algorithm for Pulmonary Embolism.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Aug 5, 2021
PURPOSE: Since artificial intelligence is transitioning from an experimental stage to clinical implementation, the aim of our study was to evaluate the performance of a commercial, computer-aided detection algorithm of computed tomography pulmonary ...
Deep learning for pulmonary embolism detection on computed tomography pulmonary angiogram: a systematic review and meta-analysis.
Scientific reports
Aug 4, 2021
Computed tomographic pulmonary angiography (CTPA) is the gold standard for pulmonary embolism (PE) diagnosis. However, this diagnosis is susceptible to misdiagnosis. In this study, we aimed to perform a systematic review of current literature applyin...
An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism.
Scientific reports
Jul 7, 2021
Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there ...
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