AIMC Topic: Blood Coagulation
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Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke.
Aging
Apr 3, 2024
BACKGROUND: Coagulation system is currently known associated with the development of ischemic stroke (IS). Thus, the current study is designed to identify diagnostic value of coagulation genes (CGs) in IS and to explore their role in the immune micro...
Effect of Retrograde Autologous Priming on Coagulation Assessed by Rotation Thromboelastometry in Patients Undergoing Valvular Cardiac Surgery.
Journal of cardiothoracic and vascular anesthesia
Dec 29, 2023
OBJECTIVES: To investigate the effect of retrograde autologous priming (RAP) on coagulation function using rotation thromboelastometry (ROTEM) in patients undergoing valvular cardiac surgery.
Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions.
Journal of thrombosis and haemostasis : JTH
Dec 28, 2022
Artificial Intelligence and machine-learning (ML) studies are increasingly populating the life science space and some have also started to integrate certain clinical decision support tasks. However, most of the activities within this space understand...
Space-time-regulated imaging analyzer for smart coagulation diagnosis.
Cell reports. Medicine
Oct 6, 2022
The development of intelligent blood coagulation diagnoses is awaited to meet the current need for large clinical time-sensitive caseloads due to its efficient and automated diagnoses. Herein, a method is reported and validated to realize it through ...
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...
Reduction of quantitative systems pharmacology models using artificial neural networks.
Journal of pharmacokinetics and pharmacodynamics
Mar 2, 2021
Quantitative systems pharmacology models are often highly complex and not amenable to further simulation and/or estimation analyses. Model-order reduction can be used to derive a mechanistically sound yet simpler model of the desired input-output rel...
Therapeutic hypothermia in patients with coagulopathy following severe traumatic brain injury.
Scandinavian journal of trauma, resuscitation and emergency medicine
Dec 20, 2017
BACKGROUND: Coagulopathy in traumatic brain injury (TBI) has been associated with poor neurological outcomes and higher in-hospital mortality. In general principle of trauma management, hypothermia should be prevented as it directly worsens coagulopa...
A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices.
PloS one
Oct 19, 2017
The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in...
Identifying Drug-Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions.
Circulation. Cardiovascular quality and outcomes
Nov 8, 2016
BACKGROUND: Knowledge about drug-drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug-drug interactions were discoverable without ...
Predictive Value of Tests
Anticoagulants
Blood Coagulation
Registries
Drug Interactions
Warfarin
International Normalized Ratio
Humans
Administrative Claims, Healthcare
Male
Data Mining
Machine Learning
Polypharmacy
Risk Factors
Pilot Projects
Atrial Fibrillation
Retrospective Studies
Logistic Models
Drug Prescriptions
Female
Aged
Aged, 80 and over
Markers of endothelial damage and coagulation impairment in patients with severe sepsis resuscitated with hydroxyethyl starch 130/0.42 vs Ringer acetate.
Journal of critical care
Dec 8, 2015
PURPOSE: The Scandinavian Starch for Severe Sepsis/Septic Shock (6S) trial showed increased mortality in patients resuscitated with hydroxyethyl starch 130/0.42 (HES) vs Ringer acetate. Different effects of the fluids on the endothelium may have cont...
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