PCI

Novel Strategy for Human Deep Vein Thrombosis Diagnosis Based on Metabolomics and Stacking Machine Learning.

Deep vein thrombosis (DVT) is a serious health issue that often leads to considerable morbidity and mortality. Diagnosis of DVT in a clinical setting, however, presents considerable challenges. The fusion of metabolomics techniques and machine learning methods has led to high diagnostic and prognostic accuracy for various pathological conditions. This study explored the synergistic potential of du...

Establishing a Classification System for Predicting Flow-Limiting Dissection After Balloon Angioplasty Using Explainable Machine-Learning Models: A Multicenter Retrospective Cohort Study.

OBJECTIVE: Percutaneous transluminal angioplasty (PTA) is the primary method for treatment in peripheral arterial disease. However, some patients experience flow-limiting dissection (FLD) after PTA. We utilized machine learning and SHapley Additive exPlanations to identify and optimize a classification system to predict FLD after PTA. METHODS: This was a multi-center, retrospective, cohort study. ...

Construction of Risk-Prediction Models for Autogenous Arteriovenous Fistula Thrombosis in Patients on Maintenance Hemodialysis.

INTRODUCTION: Autogenous arteriovenous fistula (AVF) is the preferred vascular access in patients undergoing maintenance hemodialysis (MHD). However, ...

Early Detection of Pulmonary Embolism in a General Patient Population Immediately Upon Hospital Admission Using Machine Learning to Identify New, Unidentified Risk Factors: Model Development Study.

BACKGROUND: Under- or late identification of pulmonary embolism (PE)-a thrombosis of 1 or more pulmonary arteries that seriously threatens patients' l...

Machine Learning Predicts Peripherally Inserted Central Catheters-Related Deep Vein Thrombosis Using Patient Features and Catheterization Technology Features.

This study aims to use patient feature and catheterization technology feature variables to train the corresponding machine learning (ML) models to pre...

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein t...

Deep learning reconstruction for coronary CT angiography in patients with origin anomaly, stent or bypass graft.

PURPOSE: To develop and validate a deep learning (DL)-model for automatic reconstruction for coronary CT angiography (CCTA) in patients with origin an...

Predictive modeling of lower extreme deep vein thrombosis following radical gastrectomy for gastric cancer: based on multiple machine learning methods.

Postoperative venous thromboembolic events (VTEs), such as lower extremity deep vein thrombosis (DVT), are major risk factors for gastric cancer (GC) ...

Machine learning-based Cerebral Venous Thrombosis diagnosis with clinical data.

OBJECTIVES: Cerebral Venous Thrombosis (CVT) poses diagnostic challenges due to the variability in disease course and symptoms. The prognosis of CVT r...

Machine learning-based model development for predicting risk factors of prolonged intra-aortic balloon pump therapy in patients with coronary artery bypass grafting.

Machine learning algorithms are frequently used to clinical risk prediction. Our study was designed to predict risk factors of prolonged intra-aortic ...

Risk prediction of cholangitis after stent implantation based on machine learning.

The risk of cholangitis after ERCP implantation in malignant obstructive jaundice patients remains unknown. To develop models based on artificial inte...

Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review.

To perform a systematic review on artificial intelligence (AI) performances to detect urinary stones. A PROSPERO-registered (CRD473152) systematic s...

Thrombosed Persistent Median Artery with Coexisting Bifid Median Nerve in a Robotic Arthroplasty Surgeon: A Case Report.

CASE: A 47-year-old orthopaedic surgeon presented with acute volar left wrist pain. He performed over 250 robot-assisted knee arthroplasties each year...

On the relationship between various anticoagulants and robot-assisted radical prostatectomy: a single-surgeon serial analysis.

Prostate cancer patients often have other health conditions and take anticoagulants. It was believed that surgery under anticoagulants could worsen su...

Predictive modeling of deep vein thrombosis risk in hospitalized patients: A Q-learning enhanced feature selection model.

Deep vein thrombosis (DVT) represents a critical health concern due to its potential to lead to pulmonary embolism, a life-threatening complication. E...

Machine Learning as a Diagnostic and Prognostic Tool for Predicting Thrombosis in Cancer Patients: A Systematic Review.

Khorana score (KS) is an established risk assessment model for predicting cancer-associated thrombosis. However, it ignores several risk factors and h...

Transcatheter Aortic Valve Replacement and Coronary Protection Guided by Deep Learning and 3-Dimensional Printing.

OBJECTIVE: In this case report, the auxiliary role of deep learning and 3-dimensional printing technology in the perioperative period was discussed to...

Effects of thienopyridine class antiplatelets on bleeding outcomes following robot-assisted radical prostatectomy.

This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlopidine, clopidogrel, and prasugrel) on bleeding com...

Targeting the foramen ovale is the point of percutaneous balloon compression? Comment on: Robot-assisted percutaneous balloon compression for trigeminal neuralgia-preliminary experiences.

Peripherally inserted central-related upper extremity deep vein thrombosis and machine learning.

OBJECTIVE: To establish a prediction model of upper extremity deep vein thrombosis (UEDVT) associated with peripherally inserted central catheter (PIC...