Recent advancements in deep learning have led to a resurgence of medical imaging and
Electronic Medical Record (EMR) models for a variety of applications, including clinical …

Deep learning has made significant advancements in recent years. The technology is
rapidly evolving and has been used in numerous automated applications with minimal loss …

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 embolism (PE) is a life-threatening clinical problem and computed tomography
pulmonary angiography (CTPA) is the gold standard for diagnosis. Prompt diagnosis and …

Pulmonary Embolism (PE) occurs when blood clots travel to the lungs from different parts of
the body. It is amongst the most lethal cardio-respiratory diseases after stroke and heart …

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 …

Pulmonary Embolism (PE) represents a thrombus (“blood clot”), usually originating from a
lower extremity vein, that travels to the blood vessels in the lung, causing vascular …

The Internet of Medical Things (IoMT) has revolutionized Ambient Assisted Living (AAL) by
interconnecting smart medical devices. These devices generate a large amount of data …

We present a novel computer algorithm to automatically detect and segment pulmonary
embolisms (PEs) on computed tomography pulmonary angiography (CTPA). This algorithm …

Pulmonary embolism (PE), a blockage of the lung artery, is common and sometimes fatal.
Early diagnosis and treatment of PE can reduce the risk of associated morbidity and …