AIMC Topic: Pulmonary Embolism
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Development and Validation of a Natural Language Processing Model to Identify Low-Risk Pulmonary Embolism in Real Time to Facilitate Safe Outpatient Management.
Annals of emergency medicine
Mar 2, 2024
STUDY OBJECTIVE: This study aimed to (1) develop and validate a natural language processing model to identify the presence of pulmonary embolism (PE) based on real-time radiology reports and (2) identify low-risk PE patients based on previously valid...
External validation of the RSNA 2020 pulmonary embolism detection challenge winning deep learning algorithm.
European journal of radiology
Feb 13, 2024
PURPOSE: To evaluate the diagnostic performance and generalizability of the winning DL algorithm of the RSNA 2020 PE detection challenge to a local population using CTPA data from two hospitals.
Use of artificial intelligence and radiomics for risk stratification in patients with pulmonary embolism: New tools for an old problem.
European journal of clinical investigation
Jan 24, 2024
A deep learning-based algorithm improves radiology residents' diagnoses of acute pulmonary embolism on CT pulmonary angiograms.
European journal of radiology
Jan 17, 2024
PURPOSE: To compare radiology residents' diagnostic performances to detect pulmonary emboli (PEs) on CT pulmonary angiographies (CTPAs) with deep-learning (DL)-based algorithm support and without.
A Novel Tool for Predicting an Abnormal Echocardiogram in Patients with Pulmonary Embolism: The PEACE Score.
The Journal of emergency medicine
Nov 22, 2023
BACKGROUND: Transthoracic echocardiography (TTE) is an essential tool for risk-stratifying patients with pulmonary embolism (PE), but its availability is limited, often requiring hospitalization. Minimal research exists evaluating clinical and labora...
Advancing prognostic precision in pulmonary embolism: A clinical and laboratory-based artificial intelligence approach for enhanced early mortality risk stratification.
Computers in biology and medicine
Nov 11, 2023
BACKGROUND: Acute pulmonary embolism (PE) is a critical medical emergency that necessitates prompt identification and intervention. Accurate prognostication of early mortality is vital for recognizing patients at elevated risk for unfavourable outcom...
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 ...
An artificial intelligence algorithm for pulmonary embolism detection on polychromatic computed tomography: performance on virtual monochromatic images.
European radiology
Aug 5, 2023
OBJECTIVES: Virtual monochromatic images (VMI) are increasingly used in clinical practice as they improve contrast-to-noise ratio. However, due to their different appearances, the performance of artificial intelligence (AI) trained on conventional CT...
Added value of an artificial intelligence algorithm in reducing the number of missed incidental acute pulmonary embolism in routine portal venous phase chest CT.
European radiology
Aug 3, 2023
OBJECTIVES: The purpose of this study was to evaluate the incremental value of artificial intelligence (AI) compared to the diagnostic accuracy of radiologists alone in detecting incidental acute pulmonary embolism (PE) on routine portal venous contr...
Automated detection and segmentation of pulmonary embolisms on computed tomography pulmonary angiography (CTPA) using deep learning but without manual outlining.
Medical image analysis
Jul 14, 2023
We present a novel computer algorithm to automatically detect and segment pulmonary embolisms (PEs) on computed tomography pulmonary angiography (CTPA). This algorithm is based on deep learning but does not require manual outlines of the PE regions. ...
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