AIMC Topic: Venous Thromboembolism
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An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.
PloS one
Jul 15, 2024
INTRODUCTION: Postoperative complications affect up to 15% of surgical patients constituting a major part of the overall disease burden in a modern healthcare system. While several surgical risk calculators have been developed, none have so far been ...
The potential use of artificial intelligence for venous thromboembolism prophylaxis and management: clinician and healthcare informatician perspectives.
Scientific reports
May 26, 2024
Venous thromboembolism (VTE) is the leading cause of preventable death in hospitalized patients. Artificial intelligence (AI) and machine learning (ML) can support guidelines recommending an individualized approach to risk assessment and prophylaxis....
Machine learning models for prediction of postoperative venous thromboembolism in gynecological malignant tumor patients.
The journal of obstetrics and gynaecology research
Apr 30, 2024
AIM: To identify risk factors that associated with the occurrence of venous thromboembolism (VTE) within 30 days after hysterectomy among gynecological malignant tumor patients, and to explore the value of machine learning (ML) models in VTE occurren...
Machine Learning-Based Predictive Models for Patients with Venous Thromboembolism: A Systematic Review.
Thrombosis and haemostasis
Apr 4, 2024
BACKGROUND: Venous thromboembolism (VTE) is a chronic disorder with a significant health and economic burden. Several VTE-specific clinical prediction models (CPMs) have been used to assist physicians in decision-making but have several limitations....
Interpretable machine learning-based predictive modeling of patient outcomes following cardiac surgery.
The Journal of thoracic and cardiovascular surgery
Nov 29, 2023
BACKGROUND: The clinical applicability of machine learning predictions of patient outcomes following cardiac surgery remains unclear. We applied machine learning to predict patient outcomes associated with high morbidity and mortality after cardiac s...
Correlation Between Statin Use and Symptomatic Venous Thromboembolism Incidence in Patients With Ankle Fracture: A Machine Learning Approach.
Foot & ankle specialist
Oct 31, 2023
BACKGROUND: Identifying factors that correlate with the incidence of venous thromboembolism (VTE) has the potential to improve VTE prevention and positively influence decision-making regarding prophylaxis. In this study, we aimed to investigate the c...
Outcomes from a prospectively implemented protocol using apixaban after robot-assisted radical cystectomy.
BJU international
May 11, 2023
OBJECTIVES: To compare the safety and efficacy of oral apixaban with that of injectable enoxaparin after robot-assisted radical cystectomy (RARC) for venous thromboembolism (VTE) thromboprophylaxis.
A narrative review of the application of machine learning in venous thromboembolism.
Vascular
Jan 19, 2023
OBJECTIVE: To summarize the current research progress of machine learning and venous thromboembolism.
Combining mathematical modeling and deep learning to make rapid and explainable predictions of the patient-specific response to anticoagulant therapy under venous flow.
Mathematical biosciences
Apr 30, 2022
Anticoagulant drugs are commonly prescribed to prevent hypercoagulable states in patients with venous thromboembolism. The choice of the most efficient anticoagulant and the appropriate dosage regimen remain a complex problem because of the intersubj...
Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.
Scientific reports
Jun 18, 2021
Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among young-middle-aged inpatients are different from those among elderly people. Therefore, the current prediction models for VTE are not applicable to you...
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