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Central venous catheters tip positioning: Insights from a retrospective analysis.

BACKGROUND: Tunneled central venous catheters (tCVCs) are essential in hemodialysis when arteriovenous access is not feasible. Their correct positioning is crucial to ensure efficient dialysis and prevent complications such as stenosis and thrombosis. METHODS: This retrospective, non-randomized study reviewed all tCVC placements performed from January 2017 to December 2024 at the Nephrology Depart...

Machine Learning in Venous Thromboembolism-Why and What Next?

Venous thromboembolism (VTE) remains a leading cause of cardiovascular morbidity and mortality, despite advances in imaging and anticoagulation. VTE arises from diverse and overlapping risk factors, such as inherited thrombophilia, immobility, malignancy, surgery or trauma, pregnancy, hormonal therapy, obesity, chronic medical conditions (e.g., heart failure, inflammatory disease), and advancing a...

Development and validation of venous thromboembolism-bidirectional encoder representations from transformers (VTE-BERT) natural language processing model.

BACKGROUND: Accurate and rapid phenotyping of venous thromboembolism (VTE) in longitudinal studies is important. A natural language processing (NLP) t...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracerebral hemorrhage. We aimed to develop a risk assessm...

An Interpretable Artificial Intelligence System for Crohn's Disease Ulcer Identification and Grading on Double-Balloon Enteroscopy Images.

BACKGROUND: Crohn's disease (CD) is an incurable inflammatory bowel disease that can lead to a variety of complications and requires lifelong treatmen...

A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.

Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to assist in diagnosis. We have constructed a new metho...

Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024.

BACKGROUND: Thrombosis of arteriovenous fistulas represents a prevalent complication among patients undergoing hemodialysis, characterized by a notabl...

Method for Predict Stenosis of Arteriovenous Fistula Patients Based on Machine Learning.

OBJECTIVES: Arteriovenous fistula (AVF) is the most ideal vascular access for hemodialysis. People with AVF have a longer vascular access survival rat...

Towards a dynamic model to estimate evolving risk of major bleeding after percutaneous coronary intervention.

While static risk models may identify key driving risk factors, the dynamic nature of risk requires up-to-date risk information to guide treatment dec...

Thrombo-vera: a new thrombosis risk model for polycythemia vera using modern variable selection methods.

BACKGROUND: Thrombosis is a major complication in polycythemia vera (PV), contributing to significant morbidity and mortality. This retrospective stud...

Echocardiography for short-term mechanical circulatory support: a trans-Atlantic practical guide.

Short-term mechanical circulatory support (stMCS) devices are increasingly utilized for haemodynamic stabilization in patients with cardiogenic shock....

A machine learning-based predictive model for the occurrence of lower extremity deep vein thrombosis after laparoscopic surgery in abdominal surgery.

BACKGROUND & AIMS: Deep vein thrombosis, a common complication after laparoscopic surgery, can negatively affect patients' limb motor function and eve...

Deep Learning-Based Aortic Diameter Measurement in Traumatic Hemorrhage Using Shallow Attention Network: A Path Forward.

The accurate assessment of aortic diameter (AoD) is essential in managing patients with traumatic hemorrhage, particularly during interventions such ...

The underlying molecular mechanisms and biomarkers of Hip fracture combined with deep vein thrombosis based on self sequencing bioinformatics analysis.

BACKGROUND: Thrombus formation is a severe complication in orthopedic surgery, significantly increasing mortality in patients with fractures. Therefor...

Direct evaluation of antiplatelet therapy in coronary artery disease by comprehensive image-based profiling of circulating platelets.

Coronary artery disease (CAD) is a leading cause of death globally. Antiplatelet therapy remains crucial in preventing and treating CAD-associated thr...

Impact of body mass index on D-dimer diagnostic utility for deep vein thrombosis in patients with cancer: a single-center retrospective analysis.

BACKGROUND: Deep vein thrombosis (DVT) is a common complication in cancer patients associated with significant morbidity and mortality. D-dimer is a w...

Intravascular Lithotripsy Versus Rotational Atherectomy for Calcified Coronary Lesions: A Systematic Review and an Updated Meta-Analysis of Clinical Outcomes.

BACKGROUND: Severe coronary artery calcification (CAC) remains a significant challenge in interventional cardiology, especially in elderly and comorbi...

Assembling ″Balloon-String″ Colorimetric Probes through Click Chemistry and Hybridization Chain Reaction for Dual-Signal Amplification in Aptamer-Based Lateral Flow Assays.

As a simple and visually assessable point-of-care testing method, lateral flow assays (LFAs) are widely used for detecting procymidone in vegetable sa...

Using machine learning models to predict post-revascularization thrombosis in PAD.

BACKGROUND: Graft/ stent thrombosis after lower extremity revascularization (LER) is a serious complication in patients with peripheral arterial disea...

Invited Article: Al guided Dual Antiplatelet Therapy and Anticoagulation.

Artificial intelligence (AI) has emerged as a transformative tool in healthcare through data analysis, pattern recognition and predictive modeling cap...