AIMC Topic: Anticoagulants

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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
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...

Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

Trials
BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmia diseases. Thromboembolic prophylaxis plays an essential role in AF therapy, but at present, general practitioners (GPs) are presumed to lack the knowledge and enthusias...

Predictive Factors of Early Postoperative Complications After Robot-Assisted Radical Cystectomy for Urothelial Bladder Carcinoma.

Journal of endourology
To identify protective and risk factors of early postoperative complications after robot-assisted radical cystectomy (RARC) for urothelial bladder carcinoma. Data of all robot-assisted cystectomies performed in six French centers between February 2...

Screening Anti-inflammatory, Anticoagulant, and Respiratory Agents for SARS-CoV-2 3CL Inhibition from Chemical Fingerprints Through a Deep Learning Approach.

Revista de investigacion clinica; organo del Hospital de Enfermedades de la Nutricion
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), triggers a pathophysiological process linked not only to viral mechanisms of infectivity, but also to the pattern of...

Determining the adjusted initial treatment dose of warfarin anticoagulant medicine using kernel-based support vector regression.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: A novel research field in bioinformatics is pharmacogenomics and the corresponding applications of artificial intelligence tools. Pharmacogenomics is the study of the relationship between genotype and responses to medical me...

Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm.

CPT: pharmacometrics & systems pharmacology
Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine-learning tec...

A comparative study of anticoagulant/antiplatelet therapy among men undergoing robot-assisted radical prostatectomy: a prospective single institution study.

Journal of robotic surgery
The present study aimed to assess the safety and efficacy of robot-assisted radical prostatectomy (RARP) in patients with prostate cancer (PCa) under anticoagulant (AC) and/or antiplatelet (AP) therapy, as compared to a control group, and to establis...

Development of a system to support warfarin dose decisions using deep neural networks.

Scientific reports
The first aim of this study was to develop a prothrombin time international normalized ratio (PT INR) prediction model. The second aim was to develop a warfarin maintenance dose decision support system as a precise warfarin dosing platform. Data of 1...

Systematic review of machine learning models for personalised dosing of heparin.

British journal of clinical pharmacology
AIM: To identify and critically appraise studies of prediction models, developed using machine learning (ML) methods, for determining the optimal dosing of unfractionated heparin (UFH).