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Prescriptions

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

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Showing 484-504 of 6,767 articles
DeepInterAware: Deep Interaction Interface-Aware Network for Improving Antigen-Antibody Interaction Prediction from Sequence Data.

Identifying interactions between candidate antibodies and target antigens is a key step in developin...

Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

The prediction of circular RNA (circRNA)-drug associations plays a crucial role in understanding dis...

The Effects of Presenting AI Uncertainty Information on Pharmacists' Trust in Automated Pill Recognition Technology: Exploratory Mixed Subjects Study.

BACKGROUND: Dispensing errors significantly contribute to adverse drug events, resulting in substant...

Automatic Joint Lesion Detection by enhancing local feature interaction.

Recently, deep learning models have demonstrated impressive performance in Automatic Joint Lesion De...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use dis...

DSANIB: Drug-Target Interaction Predictions With Dual-View Synergistic Attention Network and Information Bottleneck Strategy.

Prediction of drug-target interactions (DTIs) is one of the crucial steps for drug repositioning. Id...

ADR-DQPU: A Novel ADR Signal Detection Using Deep Reinforcement and Positive-Unlabeled Learning.

The medical community has grappled with the challenge of analysis and early detection of severe and ...

Interpretable Dynamic Directed Graph Convolutional Network for Multi-Relational Prediction of Missense Mutation and Drug Response.

Tumor heterogeneity presents a significant challenge in predicting drug responses, especially as mis...

Predicting Clinical Anticancer Drug Response of Patients by Using Domain Alignment and Prototypical Learning.

Anticancer drug response prediction is crucial in developing personalized treatment plans for cancer...

An efficient artificial neural network-based optimization techniques for the early prediction of coronary heart disease: comprehensive analysis.

Coronary heart disease (CHD) is the world's leading cause of death, contributing to a high mortality...

Augmenting interaction effects in convolutional networks with taylor polynomial gated units.

Transformer-based vision models are often assumed to have an advantage over traditional convolutiona...

Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations.

A variety of classical machine learning (ML) approaches has been developed over the past decade aimi...

Artificial Intelligence in Natural Product Drug Discovery: Current Applications and Future Perspectives.

Drug discovery, a multifaceted process from compound identification to regulatory approval, historic...

Future prospective of AI in drug discovery.

Drug discovery and development is very expensive and long with an inferior success rate. It is quite...

Deep learning: A game changer in drug design and development.

The lengthy and costly drug discovery process is transformed by deep learning, a subfield of artific...

Cross-ViT based benign and malignant classification of pulmonary nodules.

The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosi...

GTIGNet: Global Topology Interaction Graphormer Network for 3D hand pose estimation.

Estimating 3D hand poses from monocular RGB images presents a series of challenges, including comple...

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...

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