Pulmonary embolism (PE) is a blood clot traveling to the lungs and is associated with substantial morbidity and mortality. Therefore, rapid diagnoses and treatments are essential. Chest computed tomographic pulmonary angiogram (CTPA) is the gold stan...
AJR. American journal of roentgenology
Jul 13, 2022
Artificial intelligence (AI) algorithms have shown strong performance for detection of pulmonary embolism (PE) on CT examinations performed using a dedicated protocol for PE detection. AI performance is less well studied for detecting PE on examinat...
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...
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...
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...
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.
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...
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