AIMC Topic: Aspirin

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Real-time component-based particle size measurement and dissolution prediction during continuous powder feeding using machine vision and artificial intelligence-based object detection.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
This work presents a system, in which machine vision combined with artificial intelligence-based image analysis was used to determine the component-based particle size distribution of pharmaceutical powder blends. The blends consisted of acetylsalicy...

Predicting laboratory aspirin resistance in Chinese stroke patients using machine learning models by GP1BA polymorphism.

Pharmacogenomics
This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chinese stroke patients by incorporating patient characteristics and single nucleotide polymorphisms of and . 2405 patients were analyzed to measure the M...

Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods.

BMC medical research methodology
BACKGROUND: In randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual's risk of e...

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

Scientific reports
This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlopidine, clopidogrel, and prasugrel) on bleeding complications in patients who underwent robot-assisted radical prostatectomy. This cohort study used a ...

Machine Learning Predicting Atrial Fibrillation as an Adverse Event in the Warfarin and Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) Trial.

The American journal of medicine
BACKGROUND: Atrial fibrillation and heart failure commonly coexist due to shared pathophysiological mechanisms. Prompt identification of patients with heart failure at risk of developing atrial fibrillation would allow clinicians the opportunity to i...

Drug repurposing for COVID-19 using graph neural network and harmonizing multiple evidence.

Scientific reports
Since the 2019 novel coronavirus disease (COVID-19) outbreak in 2019 and the pandemic continues for more than one year, a vast amount of drug research has been conducted and few of them got FDA approval. Our objective is to prioritize repurposable dr...

Adjusting the dose in paediatric care: dispersing four different aspirin tablets and taking a proportion.

European journal of hospital pharmacy : science and practice
OBJECTIVES: When caring for children in a hospital setting, tablets are often manipulated at the ward to obtain the right dose. One example is manipulation of tablets containing the slightly water-soluble substance aspirin, used in paediatric care as...

Protective effect of aspirin against mitomycin C-induced carcinogenicity, assessed by the test for detection of epithelial tumor clones (warts) in Drosophila melanogaster.

Drug and chemical toxicology
The present study assessed the protective effect of aspirin against carcinogenicity induced by mitomycin C (MMC) by the test for detection of warts/epithelial tumor clones in Drosophila melanogaster. Larvae were treated with different concentrations ...

Prevalence of aspirin resistance in Asian-Indian patients with stable coronary artery disease.

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
OBJECTIVE: To evaluate the prevalence of pharmacological resistance to aspirin therapy by measuring platelet functions using the technique of light transmission aggregometry.