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Thrombosis

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Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed ...

Combining mathematical modeling and deep learning to make rapid and explainable predictions of the patient-specific response to anticoagulant therapy under venous flow.

Mathematical biosciences
Anticoagulant drugs are commonly prescribed to prevent hypercoagulable states in patients with venous thromboembolism. The choice of the most efficient anticoagulant and the appropriate dosage regimen remain a complex problem because of the intersubj...

Deep learning-based classification of DSA image sequences of patients with acute ischemic stroke.

International journal of computer assisted radiology and surgery
PURPOSE: Recently, a large number of patients with acute ischemic stroke benefited from the use of thrombectomy, a minimally invasive intervention technique for mechanically removing thrombi from the cerebrovasculature. During thrombectomy, 2D digita...

Development and validation of a predictive model for peripherally inserted central catheter-related thrombosis in breast cancer patients based on artificial neural network: A prospective cohort study.

International journal of nursing studies
BACKGROUND: Peripherally inserted central catheters have been extensively applied in clinical practices. However, they are associated with an increased risk of thrombosis. To improve patient care, it is critical to timely identify patients at risk of...

Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND AND PURPOSE: Thrombus red blood cell (RBC) content has been shown to be a significant factor influencing the efficacy of acute ischemic stroke treatment. In this study, our objective was to evaluate the ability of convolutional neural netw...

Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

IEEE transactions on medical imaging
Prediction of abdominal aortic aneurysm (AAA) growth is of essential importance for the early treatment and surgical intervention of AAA. Capturing key features of vascular growth, such as blood flow and intraluminal thrombus (ILT) accumulation play ...

Automated Segmentation of Intracranial Thrombus on NCCT and CTA in Patients with Acute Ischemic Stroke Using a Coarse-to-Fine Deep Learning Model.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Identifying the presence and extent of intracranial thrombi is crucial in selecting patients with acute ischemic stroke for treatment. This article aims to develop an automated approach to quantify thrombus on NCCT and CTA in ...

Label-free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning.

Journal of biophotonics
For patients with acute ischemic stroke, histological quantification of thrombus composition provides evidence for determining appropriate treatment. However, the traditional manual segmentation of stained thrombi is laborious and inconsistent. In th...

Cephalic inferior vena cava non-clamping technique versus standard procedure for robot-assisted laparoscopic level II-III thrombectomy: a prospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Renal tumour can invade the venous system and ~4-10% patients with renal tumour had venous thrombus. Although the feasibility of robot-assisted laparoscopic inferior vena cava thrombectomy (RAL-IVCT) in patients with inferior vena cava (I...

Blood clot and fibrin recognition method for serum images based on deep learning.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Detecting and identifying of clots and fibrins in serum is an important process in the analysis stage before laboratory analysis. Currently, visual examination is commonly employed in clinical laboratories for this purpose. However, this ...