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Prescriptions

Latest AI and machine learning research in prescriptions for healthcare professionals.

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Showing 505-525 of 6,771 articles
Development of an mPBPK machine learning framework for early target pharmacology assessment of biotherapeutics.

Development of antibodies often begins with the assessment and optimization of their physicochemical...

Machine learning integrated with in vitro experiments for study of drug release from PLGA nanoparticles.

This paper investigates delivery of encapsulated drug from poly lactic-co-glycolic micro-/nano-parti...

A Multi-View Feature-Based Interpretable Deep Learning Framework for Drug-Drug Interaction Prediction.

Drug-drug interactions (DDIs) can result in deleterious consequences when patients take multiple med...

Machine Learning-Enabled Drug-Induced Toxicity Prediction.

Unexpected toxicity has become a significant obstacle to drug candidate development, accounting for ...

HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease.

BACKGROUND: The traditional process of developing new drugs is time-consuming and often unsuccessful...

Knowledge graph applications and multi-relation learning for drug repurposing: A scoping review.

OBJECTIVE: Development of novel drug solutions has always been an expensive endeavour, hence drug re...

Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial.

BACKGROUND: Clinical decision support systems leveraging artificial intelligence (AI) are increasing...

Interventions to improve medication adherence in persons with mental disorders.

PURPOSE OF REVIEW: Nonadherence to medication is prevalent in patients with mental illness. Various ...

ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction.

Personalized cancer drug treatment is emerging as a frontier issue in modern medical research. Consi...

ExPDrug: Integration of an interpretable neural network and knowledge graph for pathway-based drug repurposing.

Precision medicine aims to provide personalized therapies by analyzing patient molecular profiles, o...

MutualDTA: An Interpretable Drug-Target Affinity Prediction Model Leveraging Pretrained Models and Mutual Attention.

Efficient and accurate drug-target affinity (DTA) prediction can significantly accelerate the drug d...

Intricacies of human-AI interaction in dynamic decision-making for precision oncology.

AI decision support systems can assist clinicians in planning adaptive treatment strategies that can...

Adaptive Multi-Kernel Graph Neural Network for Drug-Drug Interaction Prediction.

 Combination therapy, which synergistically enhances treatment efficacy and inhibits disease progres...

Leveraging Network Target Theory for Efficient Prediction of Drug-Disease Interactions: A Transfer Learning Approach.

Efficient virtual screening methods can expedite drug discovery and facilitate the development of in...

Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials.

Membrane incompatibility poses significant health risks, including severe complications and potentia...

Artificial intelligence-powered chatbots in search engines: a cross-sectional study on the quality and risks of drug information for patients.

BACKGROUND: Search engines often serve as a primary resource for patients to obtain drug information...

Monitoring of veterinary drug residues in mutton based on hyperspectral combined with explainable AI: A case study of OFX.

Veterinary drug residues in meat seriously harm human health. Rapid and accurate detection of veteri...

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