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Pulmonary Embolism

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[Pulmonary vascular interventions: innovating through adaptation and advancing through differentiation].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Pulmonary vascular intervention technology, with its minimally invasive and precise advantages, has been a groundbreaking advancement in the treatment of pulmonary vascular diseases. Techniques such as balloon pulmonary angioplasty (BPA), pulmonary a...

Pulmonary Embolism Education: Role of Generative Artificial Intelligence Models.

Missouri medicine
The growing use of generative artificial intelligence (AI) in the public sphere allows for a greater degree of disseminating information worldwide. For patients, there is a growing body of literature exploring how the generative artificial intelligen...

Extracting Pulmonary Embolism Diagnoses From Radiology Impressions Using GPT-4o: Large Language Model Evaluation Study.

JMIR medical informatics
BACKGROUND: Pulmonary embolism (PE) is a critical condition requiring rapid diagnosis to reduce mortality. Extracting PE diagnoses from radiology reports manually is time-consuming, highlighting the need for automated solutions. Advances in natural l...

Interpretable Machine Learning Approach for Predicting 30-Day Mortality of Critical Ill Patients with Pulmonary Embolism and Heart Failure: A Retrospective Study.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
BACKGROUND: Pulmonary embolism (PE) patients combined with heart failure (HF) have been reported to have a high short-term mortality. However, few studies have developed predictive tools of 30-day mortality for these patients in intensive care unit (...

Multi-Energy Evaluation of Image Quality in Spectral CT Pulmonary Angiography Using Different Strength Deep Learning Spectral Reconstructions.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate and compare image quality of different energy levels of virtual monochromatic images (VMIs) using standard versus strong deep learning spectral reconstruction (DLSR) on dual-energy CT pulmonary angiogram (DECT-PA...

Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.

European journal of medical research
BACKGROUND: This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.

Prediction of pulmonary embolism by an explainable machine learning approach in the real world.

Scientific reports
In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge because of its high mortality, high disability, high missed and high misdiagnosed rates. To address this...

A Guide for Implementing an A.I-Driven Initiative in Rural Northern Ontario.

Studies in health technology and informatics
Diagnosing pulmonary embolism (PE) often requires specialized expertise in interpreting x-rays and radiographic images, resources that are mostly limited in rural settings. This paper explores the development of an electronic health record (EHR) syst...

Utilizing large language models for detecting hospital-acquired conditions: an empirical study on pulmonary embolism.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Adverse event detection from Electronic Medical Records (EMRs) is challenging due to the low incidence of the event, variability in clinical documentation, and the complexity of data formats. Pulmonary embolism as an adverse event (PEAE) ...