AIMC Topic: Anticoagulants

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Radiomics prediction models of left atrial appendage hypercoagulability based on machine learning algorithms: an exploration about cardiac computed tomography angiography imaging.

The international journal of cardiovascular imaging Sep 25, 2024
Transesophageal echocardiography (TEE) is the standard method for diagnosing left atrial appendage (LAA) hypercoagulability in patients with atrial fibrillation (AF), which means LAA thrombus/sludge, dense spontaneous echo contrast and slow LAA blood...
Decision Support Techniques Retrospective Studies Female Reproducibility of Results Humans Machine Learning Middle Aged Risk Assessment Nomograms Predictive Value of Tests Anticoagulants Risk Factors Aged Radiomics Male Thrombophilia Blood Coagulation Multidetector Computed Tomography Coronary Angiography Computed Tomography Angiography Radiographic Image Interpretation, Computer-Assisted Atrial Appendage Atrial Fibrillation
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Prediction model for major bleeding in anticoagulated patients with cancer-associated venous thromboembolism using machine learning and natural language processing.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Sep 14, 2024
PURPOSE: We developed a predictive model to assess the risk of major bleeding (MB) within 6 months of primary venous thromboembolism (VTE) in cancer patients receiving anticoagulant treatment. We also sought to describe the prevalence and incidence o...
Humans Natural Language Processing Machine Learning Spain Anticoagulants Retrospective Studies Risk Assessment Hemorrhage Female Neoplasms Adult Venous Thromboembolism Prevalence Aged Male Incidence Aged, 80 and over Middle Aged
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Danger, Danger, Gaston Labat! Does zero-shot artificial intelligence correlate with anticoagulation guidelines recommendations for neuraxial anesthesia?

Regional anesthesia and pain medicine Sep 2, 2024
INTRODUCTION: Artificial intelligence and large language models (LLMs) have emerged as potentially disruptive technologies in healthcare. In this study GPT-3.5, an accessible LLM, was assessed for its accuracy and reliability in performing guideline-...
Risk Assessment Anticoagulants Anesthesia, Conduction Hemorrhage Practice Guidelines as Topic Humans Artificial Intelligence Reproducibility of Results
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Coagulation Risk Predicting in Anticoagulant-Free Continuous Renal Replacement Therapy.

Blood purification Aug 12, 2024
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired renal function. Typically, CRRT therapy requires routine anticoagulation, but for patients at risk of bl...
Middle Aged Female Humans Anticoagulants Risk Factors Machine Learning Blood Coagulation Aged Retrospective Studies Male Continuous Renal Replacement Therapy
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Oral anticoagulant treatment in atrial fibrillation: the AFIRMA real-world study using natural language processing and machine learning.

Revista clinica espanola Jun 5, 2024
INTRODUCTION: Oral anticoagulation (OAC) is key in atrial fibrillation (AF) thromboprophylaxis, but Spain lacks substantial real-world evidence. We aimed to analyze the prevalence, clinical characteristics, and treatment patterns among patients with ...
Atrial Fibrillation Spain Retrospective Studies Female Aged Aged, 80 and over Natural Language Processing Anticoagulants Administration, Oral Male Middle Aged Humans Machine Learning
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Pleiotropic Effects of Direct Oral Anticoagulants in Chronic Heart Failure and Atrial Fibrillation: Machine Learning Analysis.

Molecules (Basel, Switzerland) Jun 4, 2024
Oral anticoagulant therapy (OAT) for managing atrial fibrillation (AF) encompasses vitamin K antagonists (VKAs, such as warfarin), which was the mainstay of anticoagulation therapy before 2010, and direct-acting oral anticoagulants (DOACs, namely dab...
Administration, Oral Atrial Fibrillation Chronic Disease Anticoagulants Warfarin Female Heart Failure Aged Male Humans Machine Learning
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Machine learning approach for prediction of outcomes in anticoagulated patients with atrial fibrillation.

International journal of cardiology Apr 23, 2024
BACKGROUND: The accuracy of available prediction tools for clinical outcomes in patients with atrial fibrillation (AF) remains modest. Machine Learning (ML) has been used to predict outcomes in the AF population, but not in a population entirely on a...
Hemorrhage Anticoagulants Registries Stroke Humans Atrial Fibrillation Machine Learning Female Aged Aged, 80 and over Male Middle Aged Treatment Outcome Risk Assessment Follow-Up Studies Predictive Value of Tests
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A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapy.

Journal of thrombosis and haemostasis : JTH Apr 19, 2024
BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline predictors to stratify patients into different risk groups. Therefore, these models do not account for ...
Risk Factors Aged Aged, 80 and over Male Deep Learning Time Factors Treatment Outcome Middle Aged Risk Assessment Humans Neural Networks, Computer Female Drug Administration Schedule Longitudinal Studies Predictive Value of Tests Anticoagulants Hemorrhage
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On the relationship between various anticoagulants and robot-assisted radical prostatectomy: a single-surgeon serial analysis.

Journal of robotic surgery Apr 13, 2024
Prostate cancer patients often have other health conditions and take anticoagulants. It was believed that surgery under anticoagulants could worsen surgical results. This study aims to explore the safety of robot-assisted prostatectomy in anticoagula...
Robotics Anticoagulants Robotic Surgical Procedures Prostatectomy Humans Male Surgeons
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Practical use case of natural language processing for observational clinical research data retrieval from electronic health records: AssistMED project.

Polish archives of internal medicine Mar 19, 2024
INTRODUCTION: Electronic health records (EHRs) contain data valuable for clinical research. However, they are in textual format and require manual encoding to databases, which is a lengthy and costly process. Natural language processing (NLP) is a co...
Atrial Fibrillation Information Storage and Retrieval Retrospective Studies Humans Male Electronic Health Records Middle Aged Female Natural Language Processing Aged Anticoagulants
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