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Prescriptions

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

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Showing 799-819 of 6,782 articles
Comparison of AI-integrated pathways with human-AI interaction in population mammographic screening for breast cancer.

Artificial intelligence (AI) readers of mammograms compare favourably to individual radiologists in ...

Conformational Space Profiling Enhances Generic Molecular Representation for AI-Powered Ligand-Based Drug Discovery.

The molecular representation model is a neural network that converts molecular representations (SMIL...

SSGU-CD: A combined semantic and structural information graph U-shaped network for document-level Chemical-Disease interaction extraction.

Document-level interaction extraction for Chemical-Disease is aimed at inferring the interaction rel...

Retrospective validation study of a machine learning-based software for empirical and organism-targeted antibiotic therapy selection.

UNLABELLED: Errors in antibiotic prescriptions are frequent, often resulting from the inadequate cov...

GNN-DDAS: Drug discovery for identifying anti-schistosome small molecules based on graph neural network.

Schistosomiasis is a tropical disease that poses a significant risk to hundreds of millions of peopl...

Artificial intelligence in nanotechnology for treatment of diseases.

Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by...

Toward an Explainable Large Language Model for the Automatic Identification of the Drug-Induced Liver Injury Literature.

Drug-induced liver injury (DILI) stands as a significant concern in drug safety, representing the pr...

MvGraphDTA: multi-view-based graph deep model for drug-target affinity prediction by introducing the graphs and line graphs.

BACKGROUND: Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening...

MAGICAL: A multi-class classifier to predict synthetic lethal and viable interactions using protein-protein interaction network.

Synthetic lethality (SL) and synthetic viability (SV) are commonly studied genetic interactions in t...

Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions.

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. I...

Detecting the interaction between microparticles and biomass in biological wastewater treatment process with Deep Learning method.

Investigating the interaction between influent particles and biomass is basic and important for the ...

Leveraging artificial intelligence for better translation of fibre-based pharmaceutical systems into real-world benefits.

The increasing prominence of biologics in the pharmaceutical market requires more advanced delivery ...

MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction.

BACKGROUND: The rise of network pharmacology has led to the widespread use of network-based computat...

Digital Epidemiology of Prescription Drug References on X (Formerly Twitter): Neural Network Topic Modeling and Sentiment Analysis.

BACKGROUND: Data from the social media platform X (formerly Twitter) can provide insights into the t...

MMFSyn: A Multimodal Deep Learning Model for Predicting Anticancer Synergistic Drug Combination Effect.

Combination therapy aims to synergistically enhance efficacy or reduce toxic side effects and has wi...

iCRBP-LKHA: Large convolutional kernel and hybrid channel-spatial attention for identifying circRNA-RBP interaction sites.

Circular RNAs (circRNAs) play vital roles in transcription and translation. Identification of circRN...

Hybrid optimal feature selection-based iterative deep convolution learning for COVID-19 classification system.

The COVID-19 pandemic has necessitated the development of innovative and efficient methods for early...

Accelerating drug discovery, development, and clinical trials by artificial intelligence.

Artificial intelligence (AI) has profoundly advanced the field of biomedical research, which also de...

Generative artificial intelligence performs rudimentary structural biology modeling.

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in ...

Intrinsic sense of touch for intuitive physical human-robot interaction.

The sense of touch is a property that allows humans to interact delicately with their physical envir...

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