Prescriptions

Comparison of proactive and reactive interaction modes in a mobile robotic telecare study.

Mobile robotic telepresence systems require that information about the environment, the task, and th...

Leveraging code-free deep learning for pill recognition in clinical settings: A multicenter, real-world study of performance across multiple platforms.

BACKGROUND: Preventable patient harm, particularly medication errors, represent significant challeng...

AI-Aristotle: A physics-informed framework for systems biology gray-box identification.

Discovering mathematical equations that govern physical and biological systems from observed data is...

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications.

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, e...

Facilitating interaction between partial differential equation-based dynamics and unknown dynamics for regional wind speed prediction.

Regional wind speed prediction is an important spatiotemporal prediction problem which is crucial fo...

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence.

Understanding protein sequence and structure is essential for understanding protein-protein interact...

Predicting long-term progression of Alzheimer's disease using a multimodal deep learning model incorporating interaction effects.

BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) at risk of progressing to A...

xCAPT5: protein-protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model.

BACKGROUND: Predicting protein-protein interactions (PPIs) from sequence data is a key challenge in ...

Assessing the Potential Role of Artificial Intelligence in Medication-Related Osteonecrosis of the Jaw Information Sharing.

BACKGROUND: Artificial Intelligence, by answering questions about disease prevention strategies, can...

Identifying Protein Phosphorylation Site-Disease Associations Based on Multi-Similarity Fusion and Negative Sample Selection by Convolutional Neural Network.

As one of the most important post-translational modifications (PTMs), protein phosphorylation plays ...

Real-world artificial intelligence-based interpretation of fundus imaging as part of an eyewear prescription renewal protocol.

OBJECTIVE: A real-world evaluation of the diagnostic accuracy of the Opthai® software for artificial...

Algorithmic Identification of Treatment-Emergent Adverse Events From Clinical Notes Using Large Language Models: A Pilot Study in Inflammatory Bowel Disease.

Outpatient clinical notes are a rich source of information regarding drug safety. However, data in t...

GraphsformerCPI: Graph Transformer for Compound-Protein Interaction Prediction.

Accurately predicting compound-protein interactions (CPI) is a critical task in computer-aided drug ...

Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction.

Active learning (AL) has become a powerful tool in computational drug discovery, enabling the identi...

Heterogeneous sampled subgraph neural networks with knowledge distillation to enhance double-blind compound-protein interaction prediction.

Identifying binding compounds against a target protein is crucial for large-scale virtual screening ...

Artificial intelligence-powered pharmacovigilance: A review of machine and deep learning in clinical text-based adverse drug event detection for benchmark datasets.

OBJECTIVE: The primary objective of this review is to investigate the effectiveness of machine learn...

More Is Not Always Better: Impacts of AI-Generated Confidence and Explanations in Human-Automation Interaction.

OBJECTIVE: The study aimed to enhance transparency in autonomous systems by automatically generating...

Identification of Protein-Protein Interaction Associated Functions Based on Gene Ontology.

Protein-protein interactions (PPIs) involve the physical or functional contact between two or more p...

Enriching the FIDEO ontology with food-drug interactions from online knowledge sources.

The increasing number of articles on adverse interactions that may occur when specific foods are con...

Drug discovery and development: the role of artificial intelligence in drug repurposing.

Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation.

BACKGROUND: With increasing antibiotic resistance and regulation, the issue of antibiotic combinatio...