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Prescriptions

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

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Showing 547-567 of 6,771 articles
MVCL-DTI: Predicting Drug-Target Interactions Using a Multiview Contrastive Learning Model on a Heterogeneous Graph.

Accurate prediction of drug-target interactions (DTIs) is pivotal for accelerating the processes of ...

Predicting drug combination side effects based on a metapath-based heterogeneous graph neural network.

In recent years, combined drug screening has played a very important role in modern drug discovery. ...

DeepDrug as an expert guided and AI driven drug repurposing methodology for selecting the lead combination of drugs for Alzheimer's disease.

Alzheimer's Disease (AD) significantly aggravates human dignity and quality of life. While newly app...

DTI-MHAPR: optimized drug-target interaction prediction via PCA-enhanced features and heterogeneous graph attention networks.

Drug-target interactions (DTIs) are pivotal in drug discovery and development, and their accurate id...

GRL-PUL: predicting microbe-drug association based on graph representation learning and positive unlabeled learning.

Extensive research has confirmed the widespread presence of microorganisms in the human body and the...

Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect.

Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean h...

MCF-DTI: Multi-Scale Convolutional Local-Global Feature Fusion for Drug-Target Interaction Prediction.

Predicting drug-target interactions (DTIs) is a crucial step in the development of new drugs and dru...

Haptic Shared Control Framework with Interaction Force Constraint Based on Control Barrier Function for Teleoperation.

Current teleoperated robotic systems for retinal surgery cannot effectively control subtle tool-to-t...

Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction.

Breast milk is essential for infant health, but the transfer of xenobiotic chemicals poses significa...

'Applications of machine learning in liposomal formulation and development'.

Machine learning (ML) has emerged as a transformative tool in drug delivery, particularly in the des...

Machine Learning-Driven Prediction, Preparation, and Evaluation of Functional Nanomedicines Via Drug-Drug Self-Assembly.

Small molecules as nanomedicine carriers offer advantages in drug loading and preparation. Selecting...

AI-powered drug discovery for neglected diseases: accelerating public health solutions in the developing world.

The emergence of artificial intelligence (AI) in drug discovery represents a transformative developm...

Sequential recommendation via agent-based irrelevancy skipping.

Sequential Recommendation is based on modelling sequential dependencies in user interactions to prod...

Toward Resolving Heterogeneous Mixtures of Nanocarriers in Drug Delivery Systems through Light Scattering and Machine Learning.

Nanocarriers (NCs) have emerged as a revolutionary approach in targeted drug delivery, promising to ...

Nationwide real-world implementation of AI for cancer detection in population-based mammography screening.

Artificial intelligence (AI) in mammography screening has shown promise in retrospective evaluations...

Meta-Learning Enables Complex Cluster-Specific Few-Shot Binding Affinity Prediction for Protein-Protein Interactions.

Predicting protein-protein interaction (PPI) binding affinities in unseen protein complex clusters i...

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