AIMC Topic: Thrombosis

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Finding and following: a deep learning-based pipeline for tracking platelets during thrombus formation and .

Platelets May 9, 2024
The last decade has seen increasing use of advanced imaging techniques in platelet research. However, there has been a lag in the development of image analysis methods, leaving much of the information trapped in images. Herein, we present a robust an...
Humans Algorithms Deep Learning Image Processing, Computer-Assisted Animals Thrombosis Mice Blood Platelets
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Thrombosed Persistent Median Artery with Coexisting Bifid Median Nerve in a Robotic Arthroplasty Surgeon: A Case Report.

JBJS case connector Apr 18, 2024
CASE: A 47-year-old orthopaedic surgeon presented with acute volar left wrist pain. He performed over 250 robot-assisted knee arthroplasties each year. Color Doppler evaluation revealed bilateral persistent median arteries and bifid median nerves, wi...
Male Surgeons Middle Aged Humans Arthralgia Arteries Thrombosis Arthroplasty, Replacement, Knee Median Nerve Carpal Tunnel Syndrome Robotics Robotic Surgical Procedures
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Machine Learning as a Diagnostic and Prognostic Tool for Predicting Thrombosis in Cancer Patients: A Systematic Review.

Seminars in thrombosis and hemostasis Apr 11, 2024
Khorana score (KS) is an established risk assessment model for predicting cancer-associated thrombosis. However, it ignores several risk factors and has poor predictability in some cancer types. Machine learning (ML) is a novel technique used for the...
Thrombosis Prognosis Neoplasms Humans Machine Learning
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Blood clot and fibrin recognition method for serum images based on deep learning.

Clinica chimica acta; international journal of clinical chemistry Dec 20, 2023
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 ...
Humans Deep Learning Image Processing, Computer-Assisted Fibrin 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 Oct 11, 2023
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 ...
Heart Ventricles Thrombosis Tomography, X-Ray Computed Humans Deep Learning Retrospective Studies Pulmonary Embolism
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Label-free histological analysis of retrieved thrombi in acute ischemic stroke using optical diffraction tomography and deep learning.

Journal of biophotonics Jun 5, 2023
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...
Ischemic Stroke Stroke Deep Learning Brain Ischemia Tomography Thrombosis Humans
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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) Jun 1, 2023
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...
Thrombectomy Vena Cava, Inferior Laparoscopy Thrombosis Carcinoma, Renal Cell Nephrectomy Kidney Neoplasms Retrospective Studies Venous Thrombosis Robotics Humans Prospective Studies
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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 May 18, 2023
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 ...
Humans Ischemic Stroke Computed Tomography Angiography Stroke Deep Learning Intracranial Thrombosis Thrombosis Brain Ischemia
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Deep Learning on Multiphysical Features and Hemodynamic Modeling for Abdominal Aortic Aneurysm Growth Prediction.

IEEE transactions on medical imaging Dec 29, 2022
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 ...
Aorta, Abdominal Deep Learning Aortic Aneurysm, Abdominal Thrombosis Humans Hemodynamics
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Deep learning prediction of stroke thrombus red blood cell content from multiparametric MRI.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences Nov 28, 2022
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...
Middle Aged Deep Learning Ischemic Stroke Aged Male Erythrocytes Stroke Neural Networks, Computer Intracranial Thrombosis Humans Thrombosis Female Multiparametric Magnetic Resonance Imaging
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